{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>median_house_value</th>\n",
       "      <th>ocean_proximity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-122.23</td>\n",
       "      <td>37.88</td>\n",
       "      <td>41.0</td>\n",
       "      <td>880.0</td>\n",
       "      <td>129.0</td>\n",
       "      <td>322.0</td>\n",
       "      <td>126.0</td>\n",
       "      <td>8.3252</td>\n",
       "      <td>452600.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-122.22</td>\n",
       "      <td>37.86</td>\n",
       "      <td>21.0</td>\n",
       "      <td>7099.0</td>\n",
       "      <td>1106.0</td>\n",
       "      <td>2401.0</td>\n",
       "      <td>1138.0</td>\n",
       "      <td>8.3014</td>\n",
       "      <td>358500.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-122.24</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1467.0</td>\n",
       "      <td>190.0</td>\n",
       "      <td>496.0</td>\n",
       "      <td>177.0</td>\n",
       "      <td>7.2574</td>\n",
       "      <td>352100.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-122.25</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1274.0</td>\n",
       "      <td>235.0</td>\n",
       "      <td>558.0</td>\n",
       "      <td>219.0</td>\n",
       "      <td>5.6431</td>\n",
       "      <td>341300.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-122.25</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1627.0</td>\n",
       "      <td>280.0</td>\n",
       "      <td>565.0</td>\n",
       "      <td>259.0</td>\n",
       "      <td>3.8462</td>\n",
       "      <td>342200.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20635</th>\n",
       "      <td>-121.09</td>\n",
       "      <td>39.48</td>\n",
       "      <td>25.0</td>\n",
       "      <td>1665.0</td>\n",
       "      <td>374.0</td>\n",
       "      <td>845.0</td>\n",
       "      <td>330.0</td>\n",
       "      <td>1.5603</td>\n",
       "      <td>78100.0</td>\n",
       "      <td>INLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20636</th>\n",
       "      <td>-121.21</td>\n",
       "      <td>39.49</td>\n",
       "      <td>18.0</td>\n",
       "      <td>697.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>356.0</td>\n",
       "      <td>114.0</td>\n",
       "      <td>2.5568</td>\n",
       "      <td>77100.0</td>\n",
       "      <td>INLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20637</th>\n",
       "      <td>-121.22</td>\n",
       "      <td>39.43</td>\n",
       "      <td>17.0</td>\n",
       "      <td>2254.0</td>\n",
       "      <td>485.0</td>\n",
       "      <td>1007.0</td>\n",
       "      <td>433.0</td>\n",
       "      <td>1.7000</td>\n",
       "      <td>92300.0</td>\n",
       "      <td>INLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20638</th>\n",
       "      <td>-121.32</td>\n",
       "      <td>39.43</td>\n",
       "      <td>18.0</td>\n",
       "      <td>1860.0</td>\n",
       "      <td>409.0</td>\n",
       "      <td>741.0</td>\n",
       "      <td>349.0</td>\n",
       "      <td>1.8672</td>\n",
       "      <td>84700.0</td>\n",
       "      <td>INLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20639</th>\n",
       "      <td>-121.24</td>\n",
       "      <td>39.37</td>\n",
       "      <td>16.0</td>\n",
       "      <td>2785.0</td>\n",
       "      <td>616.0</td>\n",
       "      <td>1387.0</td>\n",
       "      <td>530.0</td>\n",
       "      <td>2.3886</td>\n",
       "      <td>89400.0</td>\n",
       "      <td>INLAND</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>20640 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
       "0        -122.23     37.88                41.0        880.0           129.0   \n",
       "1        -122.22     37.86                21.0       7099.0          1106.0   \n",
       "2        -122.24     37.85                52.0       1467.0           190.0   \n",
       "3        -122.25     37.85                52.0       1274.0           235.0   \n",
       "4        -122.25     37.85                52.0       1627.0           280.0   \n",
       "...          ...       ...                 ...          ...             ...   \n",
       "20635    -121.09     39.48                25.0       1665.0           374.0   \n",
       "20636    -121.21     39.49                18.0        697.0           150.0   \n",
       "20637    -121.22     39.43                17.0       2254.0           485.0   \n",
       "20638    -121.32     39.43                18.0       1860.0           409.0   \n",
       "20639    -121.24     39.37                16.0       2785.0           616.0   \n",
       "\n",
       "       population  households  median_income  median_house_value  \\\n",
       "0           322.0       126.0         8.3252            452600.0   \n",
       "1          2401.0      1138.0         8.3014            358500.0   \n",
       "2           496.0       177.0         7.2574            352100.0   \n",
       "3           558.0       219.0         5.6431            341300.0   \n",
       "4           565.0       259.0         3.8462            342200.0   \n",
       "...           ...         ...            ...                 ...   \n",
       "20635       845.0       330.0         1.5603             78100.0   \n",
       "20636       356.0       114.0         2.5568             77100.0   \n",
       "20637      1007.0       433.0         1.7000             92300.0   \n",
       "20638       741.0       349.0         1.8672             84700.0   \n",
       "20639      1387.0       530.0         2.3886             89400.0   \n",
       "\n",
       "      ocean_proximity  \n",
       "0            NEAR BAY  \n",
       "1            NEAR BAY  \n",
       "2            NEAR BAY  \n",
       "3            NEAR BAY  \n",
       "4            NEAR BAY  \n",
       "...               ...  \n",
       "20635          INLAND  \n",
       "20636          INLAND  \n",
       "20637          INLAND  \n",
       "20638          INLAND  \n",
       "20639          INLAND  \n",
       "\n",
       "[20640 rows x 10 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing=pd.read_csv('./housing.csv')\n",
    "housing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 20640 entries, 0 to 20639\n",
      "Data columns (total 10 columns):\n",
      " #   Column              Non-Null Count  Dtype  \n",
      "---  ------              --------------  -----  \n",
      " 0   longitude           20640 non-null  float64\n",
      " 1   latitude            20640 non-null  float64\n",
      " 2   housing_median_age  20640 non-null  float64\n",
      " 3   total_rooms         20640 non-null  float64\n",
      " 4   total_bedrooms      20433 non-null  float64\n",
      " 5   population          20640 non-null  float64\n",
      " 6   households          20640 non-null  float64\n",
      " 7   median_income       20640 non-null  float64\n",
      " 8   median_house_value  20640 non-null  float64\n",
      " 9   ocean_proximity     20640 non-null  object \n",
      "dtypes: float64(9), object(1)\n",
      "memory usage: 1.6+ MB\n"
     ]
    }
   ],
   "source": [
    "housing.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<1H OCEAN     9136\n",
       "INLAND        6551\n",
       "NEAR OCEAN    2658\n",
       "NEAR BAY      2290\n",
       "ISLAND           5\n",
       "Name: ocean_proximity, dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing['ocean_proximity'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>median_house_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20433.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "      <td>20640.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>-119.569704</td>\n",
       "      <td>35.631861</td>\n",
       "      <td>28.639486</td>\n",
       "      <td>2635.763081</td>\n",
       "      <td>537.870553</td>\n",
       "      <td>1425.476744</td>\n",
       "      <td>499.539680</td>\n",
       "      <td>3.870671</td>\n",
       "      <td>206855.816909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>2.003532</td>\n",
       "      <td>2.135952</td>\n",
       "      <td>12.585558</td>\n",
       "      <td>2181.615252</td>\n",
       "      <td>421.385070</td>\n",
       "      <td>1132.462122</td>\n",
       "      <td>382.329753</td>\n",
       "      <td>1.899822</td>\n",
       "      <td>115395.615874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-124.350000</td>\n",
       "      <td>32.540000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.499900</td>\n",
       "      <td>14999.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-121.800000</td>\n",
       "      <td>33.930000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>1447.750000</td>\n",
       "      <td>296.000000</td>\n",
       "      <td>787.000000</td>\n",
       "      <td>280.000000</td>\n",
       "      <td>2.563400</td>\n",
       "      <td>119600.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>-118.490000</td>\n",
       "      <td>34.260000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>2127.000000</td>\n",
       "      <td>435.000000</td>\n",
       "      <td>1166.000000</td>\n",
       "      <td>409.000000</td>\n",
       "      <td>3.534800</td>\n",
       "      <td>179700.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>-118.010000</td>\n",
       "      <td>37.710000</td>\n",
       "      <td>37.000000</td>\n",
       "      <td>3148.000000</td>\n",
       "      <td>647.000000</td>\n",
       "      <td>1725.000000</td>\n",
       "      <td>605.000000</td>\n",
       "      <td>4.743250</td>\n",
       "      <td>264725.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>-114.310000</td>\n",
       "      <td>41.950000</td>\n",
       "      <td>52.000000</td>\n",
       "      <td>39320.000000</td>\n",
       "      <td>6445.000000</td>\n",
       "      <td>35682.000000</td>\n",
       "      <td>6082.000000</td>\n",
       "      <td>15.000100</td>\n",
       "      <td>500001.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          longitude      latitude  housing_median_age   total_rooms  \\\n",
       "count  20640.000000  20640.000000        20640.000000  20640.000000   \n",
       "mean    -119.569704     35.631861           28.639486   2635.763081   \n",
       "std        2.003532      2.135952           12.585558   2181.615252   \n",
       "min     -124.350000     32.540000            1.000000      2.000000   \n",
       "25%     -121.800000     33.930000           18.000000   1447.750000   \n",
       "50%     -118.490000     34.260000           29.000000   2127.000000   \n",
       "75%     -118.010000     37.710000           37.000000   3148.000000   \n",
       "max     -114.310000     41.950000           52.000000  39320.000000   \n",
       "\n",
       "       total_bedrooms    population    households  median_income  \\\n",
       "count    20433.000000  20640.000000  20640.000000   20640.000000   \n",
       "mean       537.870553   1425.476744    499.539680       3.870671   \n",
       "std        421.385070   1132.462122    382.329753       1.899822   \n",
       "min          1.000000      3.000000      1.000000       0.499900   \n",
       "25%        296.000000    787.000000    280.000000       2.563400   \n",
       "50%        435.000000   1166.000000    409.000000       3.534800   \n",
       "75%        647.000000   1725.000000    605.000000       4.743250   \n",
       "max       6445.000000  35682.000000   6082.000000      15.000100   \n",
       "\n",
       "       median_house_value  \n",
       "count        20640.000000  \n",
       "mean        206855.816909  \n",
       "std         115395.615874  \n",
       "min          14999.000000  \n",
       "25%         119600.000000  \n",
       "50%         179700.000000  \n",
       "75%         264725.000000  \n",
       "max         500001.000000  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1080 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "housing.hist(bins=50,figsize=(20,15))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 房龄和房价被设置了上限"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {},
   "outputs": [],
   "source": [
    "def split_train_test(data,test_ratio):\n",
    "    np.random.seed(42)\n",
    "    indices = np.random.permutation(len(data))\n",
    "    test_set_size = int(len(data) * test_ratio)\n",
    "    test_indices = indices[:test_set_size]\n",
    "    train_indices = indices[test_set_size:]\n",
    "    return data.iloc[train_indices],  data.iloc[test_indices]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 划分训练集和测试集的方法"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_set, test_set =  split_train_test(housing, 0.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "housing['median_income'].hist()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 分层取样"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    6.0\n",
       "1    6.0\n",
       "2    5.0\n",
       "3    4.0\n",
       "4    3.0\n",
       "Name: income_cat, dtype: float64"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing['income_cat']=np.ceil(housing['median_income']/1.5)\n",
    "housing['income_cat'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.0     7236\n",
       "2.0     6581\n",
       "4.0     3639\n",
       "5.0     1423\n",
       "1.0      822\n",
       "6.0      532\n",
       "7.0      189\n",
       "8.0      105\n",
       "9.0       50\n",
       "11.0      49\n",
       "10.0      14\n",
       "Name: income_cat, dtype: int64"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing['income_cat'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    5.0\n",
       "1    5.0\n",
       "2    5.0\n",
       "3    4.0\n",
       "4    3.0\n",
       "Name: income_cat, dtype: float64"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing['income_cat'].where(housing['income_cat']<5,5.0,inplace=True)\n",
    "housing['income_cat'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.0    7236\n",
       "2.0    6581\n",
       "4.0    3639\n",
       "5.0    2362\n",
       "1.0     822\n",
       "Name: income_cat, dtype: int64"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing['income_cat'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    5\n",
       "1    5\n",
       "2    5\n",
       "3    4\n",
       "4    3\n",
       "Name: income_cat, dtype: category\n",
       "Categories (5, int64): [1 < 2 < 3 < 4 < 5]"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing['income_cat']=pd.cut(housing['median_income'],bins=[0., 1.5, 3.0, 4.5, 6., np.inf], labels = [1,2, 3, 4, 5])\n",
    "housing['income_cat'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3    7236\n",
       "2    6581\n",
       "4    3639\n",
       "5    2362\n",
       "1     822\n",
       "Name: income_cat, dtype: int64"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing['income_cat'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "housing['income_cat'].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import StratifiedShuffleSplit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "a= StratifiedShuffleSplit(n_splits=1, test_size = 0.2, random_state = 42 )\n",
    "for  train_index, test_index in a.split(housing, housing['income_cat']):\n",
    "    strat_train_set = housing.loc[train_index]\n",
    "    strat_test_set = housing.loc[test_index]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>median_house_value</th>\n",
       "      <th>ocean_proximity</th>\n",
       "      <th>income_cat</th>\n",
       "      <th>housing_cat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>17606</th>\n",
       "      <td>-121.89</td>\n",
       "      <td>37.29</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1568.0</td>\n",
       "      <td>351.0</td>\n",
       "      <td>710.0</td>\n",
       "      <td>339.0</td>\n",
       "      <td>2.7042</td>\n",
       "      <td>286600.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18632</th>\n",
       "      <td>-121.93</td>\n",
       "      <td>37.05</td>\n",
       "      <td>14.0</td>\n",
       "      <td>679.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>306.0</td>\n",
       "      <td>113.0</td>\n",
       "      <td>6.4214</td>\n",
       "      <td>340600.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14650</th>\n",
       "      <td>-117.20</td>\n",
       "      <td>32.77</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1952.0</td>\n",
       "      <td>471.0</td>\n",
       "      <td>936.0</td>\n",
       "      <td>462.0</td>\n",
       "      <td>2.8621</td>\n",
       "      <td>196900.0</td>\n",
       "      <td>NEAR OCEAN</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3230</th>\n",
       "      <td>-119.61</td>\n",
       "      <td>36.31</td>\n",
       "      <td>25.0</td>\n",
       "      <td>1847.0</td>\n",
       "      <td>371.0</td>\n",
       "      <td>1460.0</td>\n",
       "      <td>353.0</td>\n",
       "      <td>1.8839</td>\n",
       "      <td>46300.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3555</th>\n",
       "      <td>-118.59</td>\n",
       "      <td>34.23</td>\n",
       "      <td>17.0</td>\n",
       "      <td>6592.0</td>\n",
       "      <td>1525.0</td>\n",
       "      <td>4459.0</td>\n",
       "      <td>1463.0</td>\n",
       "      <td>3.0347</td>\n",
       "      <td>254500.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6563</th>\n",
       "      <td>-118.13</td>\n",
       "      <td>34.20</td>\n",
       "      <td>46.0</td>\n",
       "      <td>1271.0</td>\n",
       "      <td>236.0</td>\n",
       "      <td>573.0</td>\n",
       "      <td>210.0</td>\n",
       "      <td>4.9312</td>\n",
       "      <td>240200.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12053</th>\n",
       "      <td>-117.56</td>\n",
       "      <td>33.88</td>\n",
       "      <td>40.0</td>\n",
       "      <td>1196.0</td>\n",
       "      <td>294.0</td>\n",
       "      <td>1052.0</td>\n",
       "      <td>258.0</td>\n",
       "      <td>2.0682</td>\n",
       "      <td>113000.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13908</th>\n",
       "      <td>-116.40</td>\n",
       "      <td>34.09</td>\n",
       "      <td>9.0</td>\n",
       "      <td>4855.0</td>\n",
       "      <td>872.0</td>\n",
       "      <td>2098.0</td>\n",
       "      <td>765.0</td>\n",
       "      <td>3.2723</td>\n",
       "      <td>97800.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11159</th>\n",
       "      <td>-118.01</td>\n",
       "      <td>33.82</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1960.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>1356.0</td>\n",
       "      <td>356.0</td>\n",
       "      <td>4.0625</td>\n",
       "      <td>225900.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15775</th>\n",
       "      <td>-122.45</td>\n",
       "      <td>37.77</td>\n",
       "      <td>52.0</td>\n",
       "      <td>3095.0</td>\n",
       "      <td>682.0</td>\n",
       "      <td>1269.0</td>\n",
       "      <td>639.0</td>\n",
       "      <td>3.5750</td>\n",
       "      <td>500001.0</td>\n",
       "      <td>NEAR BAY</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>16512 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
       "17606    -121.89     37.29                38.0       1568.0           351.0   \n",
       "18632    -121.93     37.05                14.0        679.0           108.0   \n",
       "14650    -117.20     32.77                31.0       1952.0           471.0   \n",
       "3230     -119.61     36.31                25.0       1847.0           371.0   \n",
       "3555     -118.59     34.23                17.0       6592.0          1525.0   \n",
       "...          ...       ...                 ...          ...             ...   \n",
       "6563     -118.13     34.20                46.0       1271.0           236.0   \n",
       "12053    -117.56     33.88                40.0       1196.0           294.0   \n",
       "13908    -116.40     34.09                 9.0       4855.0           872.0   \n",
       "11159    -118.01     33.82                31.0       1960.0           380.0   \n",
       "15775    -122.45     37.77                52.0       3095.0           682.0   \n",
       "\n",
       "       population  households  median_income  median_house_value  \\\n",
       "17606       710.0       339.0         2.7042            286600.0   \n",
       "18632       306.0       113.0         6.4214            340600.0   \n",
       "14650       936.0       462.0         2.8621            196900.0   \n",
       "3230       1460.0       353.0         1.8839             46300.0   \n",
       "3555       4459.0      1463.0         3.0347            254500.0   \n",
       "...           ...         ...            ...                 ...   \n",
       "6563        573.0       210.0         4.9312            240200.0   \n",
       "12053      1052.0       258.0         2.0682            113000.0   \n",
       "13908      2098.0       765.0         3.2723             97800.0   \n",
       "11159      1356.0       356.0         4.0625            225900.0   \n",
       "15775      1269.0       639.0         3.5750            500001.0   \n",
       "\n",
       "      ocean_proximity income_cat housing_cat  \n",
       "17606       <1H OCEAN          2           2  \n",
       "18632       <1H OCEAN          5           5  \n",
       "14650      NEAR OCEAN          2           2  \n",
       "3230           INLAND          2           2  \n",
       "3555        <1H OCEAN          3           3  \n",
       "...               ...        ...         ...  \n",
       "6563           INLAND          4           4  \n",
       "12053          INLAND          2           2  \n",
       "13908          INLAND          3           3  \n",
       "11159       <1H OCEAN          3           3  \n",
       "15775        NEAR BAY          3           3  \n",
       "\n",
       "[16512 rows x 12 columns]"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "strat_train_set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3    0.350533\n",
       "2    0.318798\n",
       "4    0.176357\n",
       "5    0.114583\n",
       "1    0.039729\n",
       "Name: income_cat, dtype: float64"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "strat_test_set['income_cat'].value_counts()/len(strat_test_set)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3    0.350581\n",
       "2    0.318847\n",
       "4    0.176308\n",
       "5    0.114438\n",
       "1    0.039826\n",
       "Name: income_cat, dtype: float64"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing['income_cat'].value_counts()/len(housing)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "def income_cat_proportions(data):\n",
    "    return data[\"income_cat\"].value_counts() / len(data)\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "train_set, test_set = train_test_split(housing, test_size = 0.2, random_state = 42)\n",
    "\n",
    "compare_props = pd.DataFrame({\n",
    "    \"全部数据\": income_cat_proportions(housing),\n",
    "    \"分层抽样\": income_cat_proportions(strat_test_set),\n",
    "    \"随机抽样\": income_cat_proportions(test_set),\n",
    "}).sort_index()\n",
    "compare_props[\"随机. %error\"] = 100 * compare_props[\"随机抽样\"] / compare_props[\"全部数据\"] - 100\n",
    "compare_props[\"分层. %error\"] = 100 * compare_props[\"分层抽样\"] / compare_props[\"全部数据\"] - 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>全部数据</th>\n",
       "      <th>分层抽样</th>\n",
       "      <th>随机抽样</th>\n",
       "      <th>随机. %error</th>\n",
       "      <th>分层. %error</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.039826</td>\n",
       "      <td>0.039729</td>\n",
       "      <td>0.040213</td>\n",
       "      <td>0.973236</td>\n",
       "      <td>-0.243309</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.318847</td>\n",
       "      <td>0.318798</td>\n",
       "      <td>0.324370</td>\n",
       "      <td>1.732260</td>\n",
       "      <td>-0.015195</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.350581</td>\n",
       "      <td>0.350533</td>\n",
       "      <td>0.358527</td>\n",
       "      <td>2.266446</td>\n",
       "      <td>-0.013820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.176308</td>\n",
       "      <td>0.176357</td>\n",
       "      <td>0.167393</td>\n",
       "      <td>-5.056334</td>\n",
       "      <td>0.027480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.114438</td>\n",
       "      <td>0.114583</td>\n",
       "      <td>0.109496</td>\n",
       "      <td>-4.318374</td>\n",
       "      <td>0.127011</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       全部数据      分层抽样      随机抽样  随机. %error  分层. %error\n",
       "1  0.039826  0.039729  0.040213    0.973236   -0.243309\n",
       "2  0.318847  0.318798  0.324370    1.732260   -0.015195\n",
       "3  0.350581  0.350533  0.358527    2.266446   -0.013820\n",
       "4  0.176308  0.176357  0.167393   -5.056334    0.027480\n",
       "5  0.114438  0.114583  0.109496   -4.318374    0.127011"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "compare_props"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 273,
   "metadata": {},
   "outputs": [],
   "source": [
    "## 分层取样比随机取样 样本更具有代表性"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='longitude', ylabel='latitude'>"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "housing.plot(kind='scatter',x='longitude',y='latitude',alpha=0.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='longitude', ylabel='latitude'>"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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3bUiZvAL37l74n6cgFAYEnFeV4Gc/DbN7d4Lp06GkKEo4LMnNNenqSjB69OEF6BkZBg895KGpKYHLJSgqGt6fZF6egwcfLGT37hCmKZgwwYPXe+x9fPyxj+JiBy6Xgd+fYPny3uMSWH5/gtWr/ZSXOzEMwY4dIVpbYyOanrzmmnTef9/H1VdnHFcEcvXqKF6vYPfuGB0dFvn5+l+g5uRSUlJCfX09w7HLyQNlAmRBqA1O0x7PpwUul+u0MB41vV4ydIowqZxxAsvrhUXz4eNPoTcGvlaJXUA0AdICS4JdQF0NTJ8MVUModE8G55/vZu/eGHV1caZMcVJRoWqUhBAMNzNUW5tg5co4Dgecd56d3NyDEaaGFpUmLS+GbbsS3P9QkLaaCMKQvNdh4447HAgRQUrJtGkOLr306HSc2y0YNer4PzpZWXbmzBl6h6SUFINAwMLlMggGLUpKjk8Q2e0Cu90gHLaw2dR1dblG1gpu2jQP06YNf0r6ARYscPLnPweZNs1BTs4Z4HqrOe2w2+1UVlae6sPQjDCW349PpwiTyhknsAAuvximToQ9e+CFJ8FKQLgH4m4QLvBmQooLrp8PWf14xVkS6gNgN6Dw+O+dh5GXZ+M738kkFLJITTWOu96msdHid7+L4HZDPA7btiV4+GE3aWlqf3lZasZjfTPs3J0g1Gth2gxcLgj446xZYyfVa3LttWksXmycFk72116bzWOPtbJ/fwSv1+TyyzOPaz9Op8Gtt+bw5z93EI9Lrrsum4yM0/tPYOJEB//wD1/MCQAajeb0QsfHk8vpfXcZIYSAshIoKYKZswRrV1t4YhDuFqTnw4IxMHc6TJ/Q//ZvNcCyVpWzvrkcph9f7fJRqAjLiX3Ed+9OYBh8FrWqrbVoaLBIS1P7zc2Gr90Ke2ohxYpTtx5qeiAUUtGyjvYYoyrtfPihwahRMGGAa3CAtWtjrF+fYPRokwULbEm3kQAoKXHyne8U09sbJz3dhtN5/KpvwgQPP/qRisqNRNF4JGKxbVuI6uoo6ekmVVVu8vJ0P3ONRnN6Y3q9pOkUYVI5IwXWAQwDfvsrg3/7d0FDg0VWFsyaKSgtFcyfD/YB7ovrOqHYDf44bOlJnsBKBikpyp8K1Iw5y1IeX4dSXKAe5fkO9uyMETDtdPkEabYY48faOPfcFBobIRI59lh1dQn+/OcoWVkGb70VJTUVZs4cGTHhchm4XMmJ5IzUbDyfL8Ef/tBOa2uclBSTSMTi/fd93HRTJtOnJynUqdFoNCOA5ffj1ynCpHJGCyyAkhL4xX8JIhETl4sh1TvNyDoYwZqSnpzjaGmRRCKS0lJxQgKgqsrG5s0J9uyxkBLmzLFRUdF/xKeiwsa0BV78KRZpKeBO9ZCHQWsrVFRAX5P6AfH7AQTp6QKfT9DdfXpMNz5VLF3qo7MzQUXFwYkBkYjFiy92M2aMc9Bifo1GozmV6P9QyeWMF1igIlnuYVgrLS6GyRngSFIN1vbtCZ58MoFlCRYuNFi06Pg/5g6H4M47nbS1SUwTcnKOLdiCMZNzZ5q4nFDbDNddBkXZkJrKoPVXlZUGhYWCujoLjwemTTtzP06WJVm3Lkhh4eERPKfTIJGQ1NREmTIlyX2UNBqNJkmYXi9enSJMKmfuHfE4sSxYu1Z5aZWXQ/6MwYXIYOzeLXE6BampsGmTdUICC8A0BQUFQ4uCzZoMb32iXO0z06GsEFL60QGxGLz5NmzcDGlpcN3VUFYq+PrXXbS3SzIyBB7PF9PnJhiM43AY2GwD/6KlVKapA2lZyzqzo3sajeb0xvL7CekUYVLRAmuYfPwxvP66EhmrVimn9fPOO7F9VlUZrF2boK1NctVVJzdIe8FMKMmHQAjKCyTvL42xZUuCs84yWbToYG/C9z6AT1ZCaQkEgvCnx+HbD0NamqCo6IsprACWL+/gjTeaycy0c999FWRm9l8HZpqCyZPd7NkToaDgYBQrHleiq6xMzwTUaDSnNzpFmFy0wBommzZBfr7y03K71esTFVgVFQZ/+7eCaBSysk5MrMRisHwF7N+v6svmnQuOY9zbhYCxZer59u0Wy5bFKCkxeP/9OGPHmowapf7ktu+EgnxV+J+RDr0+aGtXQvOLzDvvtFBU5KKhIcSOHT7OPXfgGQ2LFqWyb1+E/fujZGaahMOqD+Gll6ae9nYQGo3mzEY7uScf/V9/mBQWwoYNSlx1dsLZZydnv15vcqJAf30V1q5XImjjFklTE9x+69D2faAllmEo4WVZB9/Ly4E91eDxKH8ty4KUEZgYFw4nePLJOsaPT2X+/JzkDzBMxo71smVLL4YBhYXHbmeRm2vnwQdzWb06yK5dYfLybMyZk8HYsae+DYZGo9EcC8Prxa1rsJKKFljDZPFiCASUSem4cXDJJaf6iA4SicD6TVBeBrt3x9i2NcbG9YJFF7nIzR1cZI0bZ3DOOXa2bIkzc6aNHTsMVqyAqVPhskvhl7+Js2p1BLvN5JabnUOu8xoOsZhFQ0OIjIzTwzvq5ptLmDkzQFqajaKiwYvUMzJsLFqUxqJFX/DQnkaj+UIh/X6iugYrqWiBNUxSUuDOO0/1UfSPaYLNVBGmnTtipKYKGhokDQ0JcnMH/1XbbILrrnNwzTUOfvd7VciflgpbtsJVV8ZJRJrp7YwhJQR8GURjmbT3gtMO2UnSE6mpdr7//fHY7aeBhTzgcBhMmJB6Ssbu6koQi6m+kCPl3aXRaDQHGAGf6DMaLbC+QNhscMVl8NJfweEy2V+fYOpkKC0dnljx+1UNV3lfbZaU8NGyKG8vsdPc6iU/J8AvfuVjSyADf1iQsODcCXDlnKH5iA2Gy6UrAdasCfHSSz6khHnz3FxxxakReRqN5szASPXiSFaK8EmdIgQtsI5JU5OFZUFx8ekRTRkKs2dCUQG0tTuIxyTjx4vP+hAOFZcLHHaVCk1JAZ8PRo0yaWx24HJCMOQgkGHiD0pK8wWWBR9vg9FFMKlshE7sc0hnJ3R3Q3ExOJ2Drn4Y77wTID/fxOEQfPJJiPPPT8Hr/fx8DjUazecL6feTWK5ThMlEC6wB2LkzwWOPqXTYbbfZqKr6/FyqkhIoKRGoeSHDx+GA226DZ56F9g6orITbbnOyfWeYV1+Lk5MdgzIvHR2C7m4YVwkuO7R0HxRYoZBk6dI4+/dLKioEF11kw+E4c+LPdXXw+99DIgFFRfCVrwxPZGVnmzQ1xXC5DNxucUZdO41Gc/IRgKm/wyWVz49qOMm0tqo+foYBTU2Sqqr+11uxopNdu/wsWpRHUdHRs8WamlTLmqKiz9cnd+xY+OEPlM+X16tSf//x72k88PU4nd2Su/7dztYlArcdCnJh7hzIPaQO6/nnY+zaZZGdLVi2zMLvh5tuOrWF65GI5K23wrS0JFi40MmYMSN3PJs3q5RtSQnU1kJLC5QNI7p3001pvPGGj1BIsnixVwssjUYzsni92M5LUorwTzpFCFpgDcj06SZ791okEqqfX390d8d49dUWHA6D115r5v77Kw57f9WqOC+/HAfgmmtsA+7neInFJH6/8qIyR6A60W6HjU3wxifgsMFN0wSjR9lZ9gJ01EDCC5Yd6trgCufB6FU4LNm1y6K8XIlKjwc2bUpwww22z4xLTwXLl0dYsSJCZqbBk08G+f7303C7R+Z4iovho4+gvl5FrjIyhrd9VpbJHXcMcyONRqM5XgJ+5Cc6RZhMtMAagNRUwd13H9t92+Mxyc110toaoaLiaFOoTZssMjIEQqjnc+Yk7/i6uyV/+EOUri5JYaE61pSU5IqFjgC8tAUKUiGWgKfXwQ8ugoSlPjhpMXDFwe2Fi6YdbBlktytREQxKPB5BIHCgt+GpjcKEwxKHQ3mO9fZK4nHJ8aZRB2PaNDWrs6UFpkz54huyajSazzcC9T9Lkzy0wDoBHA6Db3yjnJ6eOLm5R4uxmTMNXnhBRbAuuii5n9wVK+L09EjKygxqaiw2b05wzjnJ/XWGYoAEpw3sphJcsQRceTG88RHs2GURag2TGpMkgk4OfJxMU3DzzXaefjpGR4fEZoO77jr1rWLmznWyd2+c5maLyy93kZo6cmlbIZR/2NSpIzaERqPRJA+vF2NuklKEv9UpQtAC64RxucwBbQWmT7dRWmogJeTkJPdmbrerAmpQjYRH4ptHQSpUZsHeTkDCnHLwOMCTDT/9gcV3vudjW1MUgoIf/0OIP/whnYoKVdc0YYLJd79r0NMjycwUSXOqPxEyMgwefjgVy5KnPJqm0Wg0pxUBP6zUKcJkogXWCJOdPTJRknPPtVFdLamttZg82WTatOQrLJsJd86Cmk41u6QySy3fvj3Gr3/tg6hFRakNj0fg91u8806I++8/WDieljZ8i4iTgRZXGo1G0w+fr7lYpz1aYB2Dlh7YvB/cdji7ElynPsv1GSkpgvvvdxCLSez24xMMUkJrO2RlqIhYfzhsMC7v8GX5+SZTp9oxzSg+n8Dvh1mzDCIReVzHcSJICaGQ8u4y9D8HjUajOT68Xjg3SSnC/9EpQtACa0A6fPDrpZCQEE/A9ka49/zh38TjccmaNTF6eyXTp9vJy0t2qvD4ozGrN8ILr8OsKrj5qqFvl5VlcMMNHhob42Rng9MpaGtLMGvWCHR/PgaBIDzxZ6hvhMJ8+PKNqrXPidLebhEMSsrKdMWnRqM5Qwj4YZVOESYTLbAGoLYDInGoyFWva9qhJwSZKcfeLhaTvPxyD5s2hamstJOW5mH16jguF6xaFeNb3/KcNo7chgHI44v8ZGaa3H9/KkuWhAkEJAsWOJk1a5h25SfIijWwvwHKS9XPZZ/CFRef2D67uix++csgoZDk9ttdVFWdHk2nNRqNZsQ5PW5NXxi0wDoCS0JnWLWKSUhlSRCJqXok9xDutevWBVmzJkRlpZ3q6ihNTZKpU914PIK6ugSdnRKvd+TPYyicPRUqSiBjmBYCra2S1lZJZaXJHXecupOJxZWZJ6gUZyQ69G3b2+M8/3wXoZDFTTdlUlam8r/RqCQSkcRiklDo5Kc8NRqN5pSQ4oU5SUoRolOEoAXWYcRi8NhyWNUMwWaw+aCjBcrL4fZzB6/B6uyEd5ZY1NYJiooEKSkGOTnQ2Ghhs0F6upH02YQnghCQkzW8bdrbJb/8ZZxoVPlvPfTQqTMPnTUNPl0Hr76s+iZOKFM1WUNpOP3OO720tsZxuwUvvNDFd76TD6j6snvvdePzWUydqqNXGo3mDCHgh9U6RZhMtMDqIxaDP/0Jnl8JjY1g5sL86eDrhLtugbL8Y28fj8OfHocen5vm1iBvvhVj1kz46le9RCI2fD6LCRNsnxlv7q6GvBwoKjwpp5c0urok0aikrExQXy+JRlWB+akgJxtmjIfO/VBRAevXwdxzVHuawXA6BbGYhRAGubmH11qNGaP/LDQazRmGAHTZaVLRd5I+mppUz7gLq+AVPzR1wN4W8Afh92/DNXMgOw0qBhBEwSB0dsO4sTZKinPYsSvON75hUlR09CV+5i9KYLmc8O0HICN9ZM8tmZSXC8aPN9i9W3LxxSYu14lFr6SUiKGEnAbAbof0NPC41WvLGtp2l16q8qLhsMWll57cX4DPFyclxdR2ERqN5vQhxQuzdIowmWiB1YenbwJc1AclHtixE9Y2wqTpsHILNDRBXhpcMRfOm3b09l4vjKqAPXvBkibz55kUFfU/VlcPeD0QDKtmyhxyf+/slDz9dIIbbzQpKDj9bsAOh+Duu21DMutsaYHnn4f2dpgzBxYvPrygfulSP++/H2TWLBdXX516XEJr3lyorob99ep5aenQtvN6TW64IXPY450oH37YyZtvdnD22ancdFPBSR9fo9Fo+iXoh3U6RZhMtMDqIycHKqfAUy/Bp8sgFAGc8PE28OTC7dlgT8Cn25TAkhK21qj1po1WRfF33KaEmWHAhPEDj3Xb9fDhJzCmEgqOSD26XFBZeVDwJYude6G2AaZPUqnJE2Uo0ZennlICMj8fPvwQiopg+nT1XjQqWbo0SHGxjZUrw1xwQQrp6f3Hp+NxyfbtkkQCJk4UOJ0Hx05LgwcfUK72n4c+WnV1EWIxi337wqf6UDQajeZwTp8S4S8EWmAdQgwoybf4QAAZArwC6YFAGF7fD3nb4IJz1bo798Pjb4MU0OmDS2epBsfTqgYfp6gQbrxarX8kHo/giiuS+2tpaYPH/6KE3/ot8LdfH3lTzngcOjqgrEwVnbtc6vUBHA7BpEkOtm6NUlFhG9C6YsuWCP/n3+Ps2GlQXmZwzVUmd9119PX5PIgrgCuuyKGw0MHEiYP4fWg0Gs3JxOOFs3WKMJlogXUIRelR1qwDUmwQk9ADjBGQAV2bwNgNH3TBlsvAcoAETAHhYdkDwKOPQlcXnHeeSpudQAnSkIjFVW1Sikcdq0yC+0BLC3y0DGaerSJuR2KzwZQpsGkTuN1qEsHYsYevc9tt6XR2JsjIMDHNoy/C+vURvv1tP6vXmthMSWubHZdLcOedJ1a3dSrJyrJz8cXZp/owNBqN5nCCflivU4TJRAusQ9i0NswFs2zsedkkXiaUyAoJeBui3WA5Ic0JL70KP/gbuOIcFd06v5+arIH44ANlKVBaCsuWwdlnQ17eoJsdxqq1sG0nzD4bJh0jFXmAkkK46mLYUwPzZw8v2rO7Hv6yDFx2uHUhFPTZOiz/BN57H9o74Btf63/bG25QEazOTpg6VT0/FNMU5OYO/BF8770Yu/dIbHaIR0xCAYkwEgiRvJ5F3d2wfqOKKo4fl7TdajQazecLgU4RJhktsIBg0EIIlTbrbE3glJJ4K5AtoBfwAQ5VZzVxrEp32W1wwfThj+V0QjSqapOEOGiUOVTqG+Cl1yE9FZ7+M3zvYVWHNBhzZ6rHcEgk4OmlkNqXJv3rcvhaX0ud2bOgoxPOmzvw9g4HzJs3vDEPJTvbhpSS9LQE3d0JCortXHNV//8B6pvg1XfVrMKrFw29zuy5P0NNHRgCvvng8MWuRqPRfCHweGGGThEmkzNeYO3ZE+bxx7vZtUvy3IteMCwwIlDkgnyhFP1EcArIScDYSXD71cc/3oUXqqhJSwtcd93wi9kPpPcOZMiOzPb5A/DXd2FfPVQUwzWLIPUEzdYNocY71AKhpAS+et+J7fcAgYDE4Ti6r+JNNzl58+0EG9ZHKJ9q4/LL7Vyy6GjzTynhyRfV81hM9Vd88K6hjW1Z6twkyUmdajQazeeSoB826hRhMjnjBdbmzRG6e+C5F01IM8H0qFCpU0CPwFGhFk0rg0XTYHwpFJ7A7HqvF778ZXUzf/RxePmv8OU7YHw/qb7eXmhuVjVO9j5dUVoCV12qUoSXX6I8oA4QicD3/h1274OZU2F3LTz3OnzlFhUxW7NG+XVVVUHBEM7BNOHmC+DFj5Rn1zUnEI3qD8uSvPJKgtWrLTwewV132SgpOSiyUlIETz+Zwt69bgxDUlRk4PEcXXslJYTCkJul6s0CwaEfwy03wtr1UFykZjtqNBrNGYlOESadM15gTZzk5rs/jqvIlS0GWQ6IGxAGIjCzFDqiUJ4B+1pgfkVyxrUsZWwaCEJzS/8C60+PKn+niy+CxZceXD53jnocyYbtsH6rqrnasAOy8+DjLXDlQnj9Fdi7Vwm1FSvgwQeVNcWRvPcerFoFCxbA3LkwsRx+9OWj1/v4E1j6Hpx3Llx00fFdg8ZGWLVKucJ3dcGbbyb46lcP/0iaJowbd+y/esOAqy+Bl98G04BbhxFhzMqCRcd5/BqNRvOFweOF6TpFmEzOaIHV1QXVdQ5MbOARSmRF431NBw3MBMyogI0t0NwLbj8EfMkZ2zThvnugoRGmD1Ak73Aq8eAYYk233a5SZJu2qFqvnpjatq4R9u1T7WQAampg//6jBZbPB0uWqDqk11+HmTMPjr1xC7zwsmTf3iiudMnylXYKigzWbhVMnw7ZxzEx7oBVhJSq3mu49WiHcvZUmDJOpfuGer00Go1G00fQD5t0ijCZnLECa/dueOJJ2FMLpuEmIyVIdwxwGGBTaahxo6G9B26fpSJOUsLGWrhmxrH3HU+oSMpgTgKlpcd2Hr/7TmXrUFw8tHPKzYDiHNgXVqeQ54K7b4PJY+Ftp0o5ejzqXFJTj97e7YbCQhVZOjQt2d0Njz4rWb7Uz/ZtcUK5LrxWlFjERskoGyt3CCaNgrK84c1QLCoSLFxosGSpRXdAMHG6SSx2cNzh0p+vmEaj0WiGgO5FmHTOWIH1zhIlMiaMg701ds6e7WVlg6ApYGIzYXQJTB4DJfkQiYHbAT1BSHUfe79L98J7+yDTBXdOh7wTKDB3u4fe+gWUsMtIVSlCA7j2Yrh2oXrvzjvhuedUTdeiRTB69NHb22zw1a9Ca6uq0RJCzXh87EV46704O1cLpHCBYaOnUBBzJ0h4JY++JxizXaUTv7TwoMhq9sP6FnDZYHYhpPQTWbr4YhN7isFr7wpWroPyUpg5DNsLjUaj0SQBtxeqdIowmZyxAsvthq5OyMmGnCyBzWnjytnw+mrwJ8CWAz/5CgQseHqF2sZmwN3H+Py1+mFpNZSmQ0cQ3toNd551cs4HoLQIeoMQj6kWPqMqDr5XXg7f+56Kwh0rsiYE5OYdTLPt2gfrNkPNbpAJA7AgGzAgGDLxh6DDDsUClm2HBVOhogDag/DrDWofsQRsaYevTwd7P9+QvCkCIdQXKLfr6Pfj8RNLHyaT9l54fBkUZ8JN54y8I75Go9GcFEJ+2KJThMnkNLltnXyuvBwee0LVIt1wFaQXwT/+DJp2SWIW5MVh6UeChefB5eMgMwuKswePYB1guDP+9+6NEQxKJk+2D6nPXywmCYchNfXgujYb3HotfLIOMtJg6oSjtzuWuNpZDc+8puqhrloIs6dBb0Dyl9ckYcsAwwQrAW5LGbA6BD4hWL4PtjdChgE1XUpg1fSocraKDLXvul7oCEFBPxG9s6ZAiluJlbGjDi6PRuGZ52HXbpgxHa675tQLmv2dUNsObb1wxQzw9iMIB8NC8jZBRmNnHLpgTKPRnAboFGHSOWMFVl4ezFgI76yF7nTwd0JTtSTQJkHClk74P72waZ/A5YTCHLhlMXz8qYqynHvW0TU/eV64aBS8vw8y3LB4bP9jH0lHR4I//tFPOCz5yle8TJx49E3XslQB+o4dMGeOZPXqOI2Nki9/2WTixIN/FTcuVseWkQpp/dRZHYvXP4DUFHA64LX3ldXDHz+MEbBsygzLIyBkhw4JJQbYDaL5IGzQ5oKEhGifgEuxq9fBEHR0gc8C9wC1VYYBE/q5Vnv2wvadUFGmrBRmzYSyYaRMR4IJRbB4GuSmHZ+4ArCAZuLk6P9mGo3mdMHthSk6RZhMziiBZVmwqwaiMZUaXLoRMlPhky2Q6gJ/D5+Fnqwo7N0m+bRcsPhCaOmAXz8DibjavrsXrr3k6DEuGg0XVB405xwKbrcgPd3AZrNITT06ROP3J1iyJMzrr5tMmODkxRfB77cwDFUvNXHiwXVNE8qKDr7+cBls2wGXXQIV5UePHbXAbykLsIw0qKlXjvVpXojE4ZMeE7Il9AiV37MD7QLSgNGAIbGlC+ypELaBr+/wx2fDJC/86VVIxGBMBmwthbnTVJpyXwP4g1CYC7mZA10X9aWqswuE0X/68GTjdsBl0w9fFgqp6z7U2Ys2BPeQnvRj02g0muMm5IdtOkWYTM4ogfXxOnj9QyV8youV4Pp4E/hCYM+GihmwczmQAsTj2MIQ8tv4cI3BBTPB1wOjSpUwaGgeeBxzmGksj8fgkUdSicU4SmAlEpI//rGTHTvibNoENls6kYgdw4gDUFk58K+wuxveehc8bnj9LXjwiJ6BTVF4tA2CFmTb4LqLYMVyZfVwyXxo7IUel4nIspABICggKKEccAJRQEAcMHrA6VHPQQnMVB+cVwRFuSAT8NYKmDUZ3v4Elm9QkStDwN1Xw+h+IlOVFXDj9WrG57QqyM0d3nUdafx+ePlN2L5LCazz5sDF55/6NKZGo9EMG50iTDpnlMDaVQPZ6So6U98MF82H1dugsgBmjIFUQ2DrgO3VYazeMDaXINRsUjothQduM/hkDaxYrwTaJVcOPI7fr5zTs7OHHsVyuQxc/URoAgGLlpY4JSUGTU0RhAgzapSB3a7MOTs75VFNlA/g9UJJEdQ3wtx+Ghm/0qV+ljqhIQobJNx6yHntagCbC2wJg1jcUtGrbCAsISIhbKnIVq4gkSGw+WH0IecQT4DTpiwjEn2tdtq64JNNUF6ohEhvAF79CL71pf7P4eyz1ONQenuVZ1d+fvKK33ftgudeUA2fb7xhaCLpxddhTzWU9on1pcsgMwNmncSJDRqNRpMUXF6YpFOEyeSMElizpsDzb0GXD+ZNhwunwfZ90NwFTR0wYzJ853q47vowjcSw2yTtjSbnjHWSneHgyotg1jSVQsvK6H+Mujr4459UgfaC+bB48Ykds9drMH68k8cf76C7O8E3v5lJQYGNZ56JUlgoGDVq4K8cNhvcf58SfBn9HG/AAlefkHAK9fpQohLKI9CcAFINtUIYaLVUE2wpQSSQaRL7JBsT5hnYD9nHvGmwbR/UNisBcvHsvm4M4qCAcdghGB769WhshN/9HqIRGDsO7vxyciJGn6xQx7ZuPSy8sH+X+0MJBmHXXiWuDjQKz82GVeuUwAqFJHv2gM8nKSgQVFQwpMkLGo1Gc0oI+2G7ThEmkzNKYE2boGp+ojEozlc3xnsvhw171A3yrDHgtIPbFcNlg3jCTjQSZ/dWePppuOoqKBgkTbV+vRIQpSWw7GO45JITEwCGIbj99kzKyuz09iaYP9+LaQr+1/8yMQwQg4TI7HbIHKDG6YI0eKEDRAxMAXOPKIrPSUDTDigph6a9EIoaELHAEiqUnDAhbkGPJLwZ4kWQe8g+ivPg4ZuhoQ28bhhVoiwXinKhrhlSPdDZC5cNo8fhtm1qImN5Oezepdz4j8dF/kjOmQPP1kDV1IGv16GYpvq9Whb0dFu0t0niCSgrNfj972HZMovcXFVHFo9LRo+GO+4wcLkEO3bAli0wf77uf6jRaE4TdIow6ZxRAgsg74ibsdcN5009dIngnHMcPPNMDJvNwuOxs2OHic0GJSWqR9+xKC+HlStVn8EJE45PXMXjkpUro1RUmJSU2LDZBBdccLj6Mc3ji4a09EK7D0qzYEYK5NqgMw4FDsg/YpafEYeKVCWKHOmwLwAROyAFICBhASZkCMw0C0fUIB5ApRH7yM5QjwPYbHDXVfDROujogQtnwcxJQz/+4mLV1HpfjZqo0J8j/fEwYQL8+H8NPaXrdMI5Z8PTzyd499U4Pl8Mt0cyfZoDpPqziscF55+v1t+3T/L++xaXXmry9NPqmvb0wH33Jef4NRqN5oRweWGiThEmkzNOYA2FW29NZft2P3Z7gvR0F2Bit6s2MoMxfTqkpakU0tgh2jQcSVNTgueeCzJjhoN77hn4V+Tzxdm508fkyWm43YN/9ajrgN99BJaENDc8eCGUulQNVn8U58K4cli5AbrDYNgg1SkIGZK4RyofhriA3jiWE+q6bazezoA1YQdIcQ8vanUoEycqt/muLnV9k9V3sK0tTihkkZNjw+MZXBU3d0CnhNW7oduK47RbRMOSVZ+GyMtzkptr0NpqkkgYmKYq0P/LS5CdLxk9WkWx+nPT12g0mlNC2A87dYowmWiB1Q+zZ5vcfns61dWStDTBDTeoNFRW1tC2HzVq8HWORXGxyVe/mkJBwbFF06efdvHUU/U8+GAFM2cOntfa3aoiaqWZSmw19cDYY1gfZKXBj+6Cv1bAOx8pu4SKPMHqZYLa/XGCsb5ZhYaJR0aYOdliz/7jy4fG47B1G4TCMG7Msa91soXJ0qU+li71Y5oCl0tw991ZFBcP3BCxowd+84qaLer2ApkmZhyizTEALEvQ0WEhpUQIOyDYuhO27pA8/1c4/1z4u+uTF33TaDSaE0anCJOOFlj94HTCvfdCT48gJSV5UZIjaW+XtLRIxo8X2GwHc1OGIaiqGnzQs85SXkrjxg2t4WFppvK2qu1Qs/tyh3CDL8qB+6+FTAe8tRxysyC1wCAlaCMmJCmOGJYhSE8zsUlVZ3U8/PlFWL9RpRA9Hnjg/qHVQp0oDQ0xli71U1pqxzQFXV0JXnihm299a+Biu+21EItDYT5cfqmgpcmgyydx2iQXXmijqUmQliYwTQufX31+GhqgvFyQnytoaNbiSqPRnGa4vDBepwiTiRZYA2AYQ7vBS6lsA1yuo53dB+OJJ+JUV0u++lUbVVXDr6nKznZw8cVDN4caVwD3L4DWXhiVCxmeoW331hL4dAXs2QkfdSgrA2+6AWGL5nobzoRFTqEDQgae4fYIAgIB2LwNRlWqGqiaOqipTZ7A2rwd/vP/qUL+++6Ac89Ry6WEHXUWwYTxWU1berpBfX2sL/rU/+9EHnKOFeUG3/kbO+u3mWT2WowdY7B1p2TZGoNI1MS3RNlUpDghv9jA54erT3BmqUaj0SSdsB92n9wUoRDCBNYADVLKK4UQlcCzqEretcCXpZRRIYQTeBw4G+gAbpFS1vTt44fAfUACeERK+Xbf8sXAf6Hicr+XUv5b3/J+xxiJ8zvjBdb27UognXXW8CNV8Tg8/zxs3apmi9155+D1R4cyfrwgFILc3KGLq+XL6yguTqPiQJO/YTIqVz2Gw9YdUFkOKWnw1/egshjKiyAzzWDLdoMUqVzimwKqJunyxUMvFgd13Z0OVbfmdquZee4h9nwcjHgc/uGflW9WQsL//Aaww9Y2aOmG5k4b6ztSyMiKUJQJTU1xcnIc1NRIKir6n6U5vgyWrFWpQrcT2n2CmxabjM9x8tjjUXY1mngzJIkeG02dgtlTIL/A4AePCDLSBz63WExSUxPB6TQoK9M9CjUazUnk1KQIvwlsR/UGAfh34GdSymeFEL9GCadf9f3sklKOEULc2rfeLUKIScCtwGSgCFgihDjg+vhLYBFQD6wWQrwipdx2jDGSzhktsPbvh8ceV+1vfD64+OLhbV9TA5s3Q0WFck1/4w34+tfVe5Yl2bo1gt8vmTzZQVra0Z/cyy+3cfnlwxszJ8eD13tyb75TJsEHy9XsvaxMaAuBvx7Ks6GoEIwQfLgfqqXqG/jmHrh8GAX+djvcfotq7NzeCfPOgXHHOUHgSHp6IBZRDbxdbkhLE7ywCmpN8LfC2GyTcROctLaHifti5OTYaWlx8etfR7jnHgcTJhz9e8vLhK9eCe+sBn8ILp4JF0wHm83G7XcaBJ+VjC4XrF1vUFsPOfmQkQ7paQOLq0RC8vjjHezdG0FKWLw4jfPP13lEjUZzknB6YezJSxEKIUqAK4CfAH8j1LfZhcDtfas8BvwjSvxc0/cc4M/A/+tb/xrgWSllBNgnhNgDzO5bb4+UsrpvrGeBa4QQ248xRtI5owWWaSrPqjhgHEO5x+Pw0UfQ0gLnnQelfW1dDgQ3pIREQu3vAB99FOKNNwLY7YJPPgnxyCOZ2O0nbjQ5fvwgDpgjwKULoaxYNW1ufR1qGlXUyR+EX34fXHb4+rMwpgdyLHh3G1wyGmzDqHcfMxp+9P0+S4gk6seUFBhbDhs2S6ZOh7asBPUZBj1+A7NQpU09bjtzp2RTmSpJJAQ//3kEv//w3+eRlOTBvVf0s7zQID0dEDB1CrR2gDcFbr9B1ZYNREdHnOrqCBUVTqJRi2XL/FpgaTSak0fED3uTliLMEUKsOeT1b6WUvz1inZ8D3wMO/KPLBrqllAc6rtUDxX3Pi4H9AFLKuBCip2/9YmDlIfs8dJv9RyyfM8gYSeeMFlhFRWrKv99/eMPkI1m1Ct5+W9kv7N4N3/ueqrmqrIRZs2DtWlW0fOUhbWZ2746Sm2uSnm5SVxejt9ciO7v/O/bevRZr10quvloZUZ5umCYUF8GrS6GxBVwmlBRA1QTJh+9F+Y+fWWzca2Biw+42Sc+D+RZcf93wxjGM5E8ocLng298SPPU0NLoT+C8K0d3t4CKng0hccNt0+OUGeGKn4OGzBEVeePBBJ6GQpKho+DMiszJUu6EX31KGtt95AC6eN3jKNCXFwOEw6OhQdhEVFTpFqNFoTiICSF4f1XYp5cwBhxLiSqBVSrlWCHFB0kY9zTijBRYokTQYPp8qYM/Kgvp6lSpzuZQguPZa8KRA9V6VLszNVTPhpk1z8tJLfjo7E5SX20lPH/iT29Cg6rgWLaLffoQAkYiF3S6S1m4l3NeeZqDxjmTLDvAHYOF0WLNH9Te8vCrOd78doaE+CCRIYBBPTSXd4eXpp+GihahozimmvBz+7oeCloTgMQn+VouCTjgnX80GDEQhNwW8fc4MTpdgyccSxyaLxRcaw568MHkcTBqrIptHGs1KqfoeCqF8vA4Ir5QUk3vuyea993ykphosWpR29I41Go1mpHB6YcxJSxHOA64WQlwOuFA1WP8FZAghbH0RphKgoW/9BqAUqBdC2IB0VLH7geUHOHSb/pZ3HGOMpHPGC6yhMGuWEkD19XDBBYeLhjVr4c03Vfpn5y4VgbngApg9201eno1g0GLUKPthNgxHMn++YNYsgdvd/zo7dgR46qkm8vOdfOUrRbhcJ1aJGA7Df/1BPf/mfUMTWXa7Kj4vzISLpypPrKY6i4YGHyBRX30SWL4eQl43NftN/uO/YPEiOO/cEzrcpJFvmvyN9GIUglGkrvXHdeABvjYV0pwgpeR//39h3v8ggrQE1budfPvhIarQQxCi/6jVjh3wpz+p9+67D8Yd0oS7rMzB3Xcnoe+PRqPRDJeIH/adnFmEUsofAj8E6ItgfVdK+SUhxAvAjahZfncBf+3b5JW+1yv63n9PSimFEK8ATwsh/hNV5D4WWIWKx43tmzHYgCqEv71vm/cHGCPpaIE1BLKy4FvfgljsaCuGrdtg8w5VvBwKQfwdqPXDzIkwefTAZpWHIoQ45qy57dv9SAn19WE6O+MUFSVhqkef1cChlgPHYtokWLcZtu9WDZq/dD3U7jUO7uizKSgJ4qEAZaVu8vLsvPBXdf0mjT/xQ04GtiNUz9xSmJYPqX2/1/37E+zcFiE9wyRhwZrVYTo67P2mdz9YAdW1cO3igZt/H4mUB6/5UK+9RqPRjDjJTREeL98HnhVC/G9gPdAXCuAPwBN9ReydKMGElHKrEOJ5YBuqnPpBKWUCQAjxEPA26sb0Rynl1kHGSDpaYA0Rw+jf5yocUcLL44buCGyqg7Jx8Mzb8MitkDdE9/djMW9eJq2tMYqKnBQUnHhtjssFj/T1wBuqHYLNBg4DrBgIA1wOWLDARlmpnbq6KGABkuxcweRJUWprQry/LJ2WLheJJ+HLN8Cc6YOPs2StmniwcMZxntwwMcRBcQWqyH5UGQRjglAQDEsJ5yOJRpW7vT8A40bDebOGNt7EiXDPPSqCdWj0SqPRaE4pDi9UnnyjUSnlB8AHfc+rOTgL8NB1wsBNA2z/E9RMxCOXvwG80c/yfscYCbTAOga13aqf8ahjiKQxY6Cqqm9WXR2YTuWN1BNQs+yGKrDaO1SbmNJ+5jPk5Tn42teO0yJ9AIbrM7V3H+ytUfVFPj+89g78zQOCd97J4mtf66C5OYbPB6mpcZqbe+n1mdS3BDnvwgLGj3Hz+gdw9hQl1I5Fcc7wPLSSTUmJyejRNtavT7BtkyQnx87KlQY33nj4eg4HXH4h7NsPk4dhKSEETBpGc2uNRqM5KUT9UKt7ESaTEQ8ICiFMIcR6IcRrfa8rhRCfCiH2CCGeE0KcltOl9nXBb1bDb9bAzvaB15t3Dpw1DVoCIB0QFfDachhdDKUFQx/vj8/CLx+Fnt4TPvQRwTBAWgctKWx9GbPx4+0sWZLPb36Tw4IFLhIJi94eQWmJg2jIZNWyHj5dHiYeG5pwmlgOEwYxa43HJS++mKC+Pvk5NodDcO+9Kcyb52H69BQuuMBDTU3/B37ebBWZy8xI+mFoNBrNyeVAlUcyHhrg5GRcDzi1HuCAi+oYoAvlonraEbfUw5Lq50B4PPCVu2HOPLjyYrj1UpgyCm5YCPZhxAfnzYK5M5Vn0unI6EolJOsalP3AtYd4QNlsglGj7HR0pAAeLMukpdmOlYBen4clb0DrbouenuQci2Up9/3oMJob+HxqksJQcDgEFy+yk3DYqa4VLFp0fMep0Wg0nyuMJD00wAinCIfp1HpaMSYL7jpLpQgnDsHb85yp8PIH0NkDU8dC+jA9IuedlIzw8WOacMt1cMUiVYtmP6J+3+22MXGioKoqkw8/NNm5M0Fmpg2320lpaQKnXVJXpwreTxSHQ3DXXSZ1ddDUBIWFg2/zu99Ba6uauTd2CCm9Vj/E86C0EKZNO/Fj1mg0mtMahxfKdbPnZDLSNVg/Z+hOrYchhLgfuB+gbDgN/pKEEDA5b+jrz5kChTmq6L2y+NTWEY0kXu/Ry3btVTVZDW2SrtYI9fV2HA4blgUFBTHsdju5uQb5+ZJoVAmkE+WDD+Cdd9R1vvNOmDDh2OtnZqq2OcdyUwc1YaG+Ff68Gmp6oC0ASz6Gi8874UPWaDSa05eoH/brGqxkMmIC60SdWvts9X8LMHPmzM/FhPayYdRcnY709lps2hQlkVD9E3NyBk+mh0Lw1J+hozXEm682Ew6BaRpkZqTg9riYMcPJHXfYyM6WPPGEn2BQcvfdKVRUnNhHb/duyMiAQABqawcXWHfdpVKKx/L8au+A3zwBr6yA5jgEguBMhR/8HH4SVS2DTibBoOTVV6M0NlrMnWtjzpyh2X5oNBrNsDk1zZ6/0IxkBGu4Tq1fKGJ9Rd2DzZo7XQgELH77Wx9dXQmEEHz0UZhvfCNtUJEVTyhrgzf+2kYkJEEKYtEE3d1h5s71kJZmY+NGwdlnx+jstHC5BJs2xQYUWIkEbNsLgRCMr4DMAZzgL7gAnnpKRaSmTx/8/AxjcEPV1RuVQ70tofouRi3Idqk2SMtWHhRYUio/sHgcpkw42q09Wbz7boyNGxPk5gr++tcoxcUmJSW6wEGj0YwADi+U6hRhMhmx2/9xOLV+Ydi3Dx5/XAmsu+5SrVpOd6qr43R2WlRUqChJXV2crVujnH/+sf0cUr0w5yz45f894OYuEUJgs8WZM8dBerpgXw3ccIONwkITv18yY8bBSIwllZA5YE7/+oewfL2apfieGx76EqT1pSWjcdjZAOlu5SH193+vxM2xmjL3h2UpIeVyQd4h9XVejzqeUCuYLZCSDs44VJZDwSEG63tr4NHnlNC6+xaYPEImql1dkrQ0SEkRtLWpiJZGo9GMCDE/NOoUYTI5FfGVk+aierIIx8FhKtNKgA8/VD5JlgUff/z5EFiGodrEHEBKiWkOXisVCsGWLTBxoocd2wOEwwIrYTFrVgpZWTba26GgANLSDB55xNvXn0/td3MvvNoMnWEo88DNxbBqs6phMwzY2gCPrYOsdAg1wS+fgpYWyEqDh26CRXNUGq+yTAm9ofLuh/DBJ2CYcM8tMKavH+WcGdDjg1AvGDGwOVQEsigbrrvq4PZ2uxKAlhx8pmhHB7z4IrS0wtQpcNllQ29off75Nv70pwQ+n0VpqUl5uY5eaTSaEUT/i0kqJ0VgDcWp9fPKymZ4tQYKPXDfJHDblKDa3mdMUVEx8LaRCDQ2qt6GA82uC4cla9dGEQJmznQkpUC8P8aMsVNSYmPfvhhCCLKyTKqqBlcCPT3qcf2N2Sz7wKSjI8aMGU4SiTTeXArFBWrmHqiWQEKoyM9bjfCDTVDfAbEQGFH4QwosTEBjG9hTYF0cZC/sWA4bV0NnqxI2vmZ48mVYtgzKi1Ua8aF7hm6eum0X5OZAdy/U7D8osBwOuHIRXLYQliyBPXtgahXMmX24i395CVx+FcQs5eI+EJYFjz8BXV0WlmXxzruCnqCJ3QuTxsC0icc+zspKk+98x4XPB/n5Arv9CzpzQqPRnHrsXijWKcJk8jmpEDp9Wd6s6nQaAtAUgFHpcP75UNwXhRk9wA04FoM//gnqG5Ro+Mp9UFp69HqvvRbi448jhEJQX5/g5psHmQZ3nDidgq98JZU9e2JYFlRW2vB6B/86s2sXbNgAPr9BZWUG994HY0cLnnpV4M4Dww6iL4Xn88PTL8Pb2+DTVOgsgFgnJPxAFDalwI69cLYLqibD2FGQbYeeNuhogkQPxB0WpAq21QvyU6GiFOrqob2zfxf8/ph/Drz8pkoRTumnON404dJL1aM/mnvgjWoVwRpVAuWHpA+lhPoWaGmGfbth505Jd1eEnl6LcAg21zu5ZJGNLbugoqR/O4/eXnj5dUhPgysuNQ5rLq7RaDQjQswPTTpFmEy0wDpBzs2H12uhMAUK+rSPYQzeZ66tTYmr8jJobIItW/sXWNu3x9i61SKRgPb2MJdf7hqS8DkenE7B5MlDN9YPBuHtt5Wb/Tvvxnn1JXj95QRer0nJJINz5xukesBmk3z8cYznX4qzq8FgV56DQJ1BNA5WGxAFTAlxiHbCaqcgLQrTssAKw7aNkGhHOb76gR5JVx74woKaOshIh5xh+GvNnAYTxqj0Xn/9JQfDZQePHRIS3Edcro83wCsfwKdLYNo4WL/RoqNLMmGcCSEQloUvAKkpA6cXN22FzVvV52j6VPUZ0Wg0mhHl9Gj2/IVCC6wTZG4hTMsBpwm2YXw4MzIgxQN1dRCLQ8kArQZzckzi8RheryAvz8b27RY2m0FpKeQMwQB1JBFCzaT75D2LDesgHhc4HCbdQYvuHYLxEy3uu9ngN7+K8v77UWxOwe6OBD2NCeKpHqxuAXZUEVtYwh4LlkN8qp1PUwyKClRa0B9CzUHtQf0TsAMOyeJLBQunqRostxta2sA0ICf7WEet6M8xX0poboGC/GP7mGV44FsLVQQrzQ3+CPgikO+FPfshrW/fPT4oqBQ0tEuqayTjR8W5406TUeMcFBeoBuH9MapCRa/SUlUqU6PRaEYcuxeKdIowmWiBlQRSjsOeyOOB+78KO3aqm+j4AWaiTZ/uoLpakpUl6O2VbNki2LhR1Xl9+9vHf8yWJT8rNj9e3G447zx47TWJZYHXaxGMCSKmiS0qiSUEL/8V3n0rTlaWgd8vsARY/gRGlgU+EzyW8l6pSUCbAdkW7IgTTHOwZyXYBZgpkOjqG9SDini5DCZPhulT1OLlq+D1JSAMuPkqmDZ5+OfT1QWvvgnXXgl5ucde19tn+dDcC79bCaEYTC+GC86GJ96ABZdAVTFMnmJQ0+gk0BmlrMTOzJnOQa07igrhh99RIm+kLCA0Go3mMGJ+aNEpwmSiBdZJJBiCUAQyUmHFCti7VwmrY6UTZ8+2Ew5DbW2cyy6zE42a7NyparyOl3ff3cuGDc088sgcnM6hfwR8Psn69ZK8PJgwQd35Fy2Ct94SNDVZBKMGpkMiDDAd4PZAWzPk5AjAIjNTkG5IKAZ/DviiwC4gbEGOCV0WzDRBCqygJCdTUOiB1dvA5wKchhJYEciZBnUZB49t1XoliqJRWLvp+ARWVhbccj3Dqnna0w6ROJRnwsYGuHoy/P19ShwdiIJNnmBjuH9qw7We0Gg0mhNCpwiTjhZYJ4n9zfDHv0IkBl4J3fshOxu2bVORoIH63Zmm4MILHcDBYp9JkwZv+XIs0tNd5Od7Mc3h/TW9+KLF9u0ghOThhwVFRQKXC37yE0EkIvnzaxaGIXE5BFXTDR68y2DPVvgw4mDv3hA+X4L0DMiqsrPXMnC0Q9QhINuAfKDQBhLoAcMhCALb98FZoyA+Dva2AC5ISYXbboWaPg8th6G8qN5brkTN/DlHH3s0KrHZGDRqN9yC8vJMNWZNF4zLAaft8PRiZyds3Kh+Z/n5/e9DSsl//3ecDRsk//APNior9X85jUZzkrF7oUCnCJOJFlgnieUb1GzBgmx4+y2YUKD644XDqmHxcBoK99cPcDjMnl3M7NnDD4ElEiplZVnqcYCMDMGvf21n2u8tPv5UEE1AUbHAZYcrr4R4wkZqWgo52QnmXyR4V5iU1AreXgG+MkEoYMAeYBTQAHabYHQ51DRBiQ0WngXtAUgYYBsHDgukF7JtKoUIcPEClVprbD26+XNrq8WvfhWlqMjgK1+xI5LQKHLfftiyE2ZWwSPzoScEZZlH12698ooSWFu2wMMP97+vUAjefFPS3CxYuTJxlMCKx1VE64va31Kj0ZwGxPzQqlOEyUQLrJNEbiZs2KWel5RBpFcVuFvWwPVXpxvXX2+wapWkoEBQUnL43d5mEzz0NZPbb4b3l8PyNdDdA81u2NsNziKDCxcanD0ZykPwmAmd+2D/HogmDGr3SxJl4M2GVJugajKIEIy2IC9TFaXvaoACAZ5y6F4JCyagmi0B0Ri8uxLaOuH91XDdxTC7Sr0XCCgR09FhYVknnn6LxeDRv6ii+J3V8N37IXcA0VtRATt3wqhRA+/P4xF8+9sGmzdLFi8+/E9y1Sol0srLVVPr45n1qNFoNIOiexEmHS2wThILZqifbV1w55UQD6nIVUkJlH1OpuFnZAguuWTgMIoQkJ0F1yxWruhFBfCzx8DtBFcqvLwUpoyFAjecF4NdvWCkgCcf5pYJanqgawx07YS6bVCVAfYsqG1WYua+S+G6C+Dffi6JROD9WkF5Plhp0NIOrV3KBb7XD+u3HxRYlZUGDzzgIDVVDMmdfjAMQ9XRNbdB1iCBwAsugNmzBzdBPW++jbLRyvrhUJYsgdxcqK6G+vqBfdU0Go3mhLB5IU+nCJOJFlgnCbsdLjqiNqiy8tQcS7LZ3wlPL7V4+ZkEHbstzp0l+MXP7JimwGaqurOEpYTJAXnT3AoV2TBjlBJHf/8ArN4AOxphuR+mjYXmZrhyHnjdkmgEyooS/OIXMf78vCQUgdwSB9YMG7Z0VWi+ywSjGbo6YN4MJcoOpNXKygy6uuHpP0N2Jlx0/rEbcdfUSJ580mLUKLjlFuMwYWaa8JVboKkVyoaQaR2sXi4Wg98/rwSb3Q7fuB0K+mYxTpsGy5er2rDcQWY2ajQazXET90O7ThEmEy2wkkjcAlOcWK1MNAa7atRNfFz5qZtNFggop/PBxm/3w/99E57/RZSW3QKbgJaXEowbCz/6oYMbL4WnX4feANx86cE+fLOqYMtuaGyBS+er5fNmw7mWaje0dQ8U5kBumuSpJ+Ns2BBn1aoQ9fU9xON+IMGODWmsXlfEpIUuRk+GnEporAarEzZtVPYZ11x28Pex5EPYul35jpWXwoRjzN7cuNEiGIRNmySLFx/dyijVO3j/ww3bYV89zD0L8o/hZ+ULKJFZUQI1DUpoHRBYl10GM2dCauqJTWzQaDSaY6JThElHC6wk8cp+eLUJxqbBg2Mgpe/KWhJ6ImqmW8oAJunxOKzdBU3tqtlxPKJEwazJcOMlJ+8cDvDGG6pJdUEB3HvvsYvqm3uhbpdF62aBtOJEjSgy7mTvHlUFX1IA37vv6O3KiuB7X1WC8tB2MeEw3Hq5SvN5PUrg1NVZfPppjLq6BFIGAAvIAcNFuC3I+qV2GhtMUgtgeiVcNFNFr1athwXnQlam2rcVh/Z2yMtXJp7BIGzaDC4nTJ16uJicM8egsdGiokKQmTn8a9jWCc+/pSY27G+GR7488LrpqTCmHPbUqnMuKzr4nmEMPPtQo9FokobNCzk6RZhMtMA6QfwheG49/NsaCPXC8gI4JwsW5EEgCk9uhf0+te7F5XBB+eHbSwl/+RA27FYmme+vh4nlMHM8bNgJ1y48dior2UQiKiVVVga1tVBTA1OmDLx+TgrIOKivPyGMeAyA6dM8PPGE2t/11x8eAbIs8PlUVMbtOrh86Qew5AOYMhFuv1mJzJISQTAoicVAymjfmimAAyzlryV9YXo6UnCmq1Y7iYS6roY4eO3274cNa4AIXL5QzTj87e9gX41a/+I2uGTRwWMpKBB84xvH/3XOblNjRyLKsf9YmCZ8+Vpo7VBia7D1NRqNJunE/dCpU4TJRAusE+Q378GvPoG96wAJDSb8pwR5o6ozqvdBWZpKH769DyoyoOIQr6X2Hti4F8ryYf1WaG+CN3dDwz6YPunkT813OFRPxNpaVQ80WN1PQTr8y/2C7e8K9m52YgjJOefYmTnTwV//qkTGJ58ouwZQwufZZ2HzZjV78s47D7qVr9+o0m5bd0AwKKmvj+P1Ch56yCQWM3n9dejttQMJMCIgUgAb2CQJC6YVw9XnqYJwn181gm5sUtGqtVtgzW5IdUNamooa1taqPn9+v9ommWSkwdduhpYOleodDJsNinSkSqPRnCp0ijDpaIF1ArxbC7+qg1oHUAViB8ggvPcxjLkAIl0wqm/2mM1QEZXuMHCIwEok1PLmNtXgt2kdBPzQuRuyXPDux7D4/OM7vnhcPVyuwdc9gBBw990qcpWdPbTC6inlgm0r7ezaZcOyvEyYIKiuVpEZy1KpxgOEQkpclZcr+4LeXtWXEeCKxfDWEsjOktzzlQA11RFSPJK/+zsv3/uek3POyeYHP4BQyALhASMGGR7S82xUVcHMSfCl66G7G/77d9DTA48/C1deDp9uhjlzoL0TWnpgsk3N7vt0lRr7oouGfo2GSnG+emg0Gs1pj+mFLJ0iTCZaYB0nbUH43SYozQZfB7Q6QRaA0QbOXFVIXemFjk5VbB1LqHqsrCOm6+ek95mProGNKyDkAyyI9cKu7bBy3fELrFWrlBXEDTcMbzuXCyZMGN42hgETJhwMt40ZAw89pATeoTYUbjfMmAHr16vUY1rawfcmjoeGBvg/P7dYtUJgmk5siQDf/Laff/pJDi0tNs45J5OPl8eIJSQixSAn3+DGa0ymV6mC8jffSzB1nEBaBgWFUFsPH6+CT9dBQR6UFEJXjxrvqivh7Bnq97J1Jzz6FJx9FkydpN7fVwOdXTC96uhi/8ZmJY5LT6Bl0bGQEroD8MwSqK2Bb98BBbrxs0ajGSkSfujSKcJkogXWcdISgHQH9CRg2kTJnoYOfKZBrDCLS84FTxC+PBFes2BPl4pSXTlGpQsPxWaDK+bBmzuAOKpVjFA/w2HwDuCftHIbvLsGplTA1fP6n+03bdqx+xyONEV9xdqWpZpB22wCIeDGG+Hyy9WsuCNToKvXQzAkSMQS+H0GRAQdHVG+8/0AUyalcP31LtweyZq1BrljTQqKbIyqVDvx+xP8+g8hbrrcZNYMN6vXqehYYytkpkNTC7S2wwN9BeeGoXzIXnoNVq+D9DRl4/C1u8GdBf/zR4iHVYpx7JiDxxiLwW8eg3gCfvStE5/d1xqE3pikJS5JMQR1QcGqXbBxD/Tshc5WyFoC37/1xMbRaDSaAdEpwqSjBdZx4rZBjhNKUsHybmLh3J10h8EVPIsicyw7YmHWiyjXTHXjiNmxGeAa4GpLA2ZMgtx74bnfQCIC7kyYMB6uvAiWNcCKJjgrF84thLou+MHbql5qzTqYPArGlRy935QU9ThZBIOSZcvidHdLZswwGTvWpLPT4ve/jxAOS+6+20lZmYkQRx+XZcEnK1XxezSCUp5WTClTy6SzKcjulBS6egymT/MwaWKCMVMNdjQYeNxQ3war6wwy853s9Av+/ma44hLYsA1efhsumqfqsjq6ICrgdyugKwRnFcGefZCfq6JrXb3w3A7oLoTqPMgLQs4RkSO7XVlKxGLDS78eoK0T/vwOFOfBtLPhnz6VvC4ksQI/UenA2uMgp8vAbFERvgw3bO447l+LRqPRDI7phUydIkwmWmAdJ5UZcFY+rG+BeG4tDU4v2RmSaM8+draU017UynYn7Bc+7nAU4jxGm/LsFPXlYeo8NZNw6xbIy4av3gQ7gP/4WL2/pBbGZ8GWVog5wRmGNgm1AUh2oGrfPlUrVVWl2r0MhpSSp56KUVtr4XYrH6mvfU3Q3m7R2WnhdgvWrYtTWmrS0AGZXkg5RJzsrYZXX1cBvDGV0N4mqQsZEFMt3gN+k3BnmOp9DjzOBELEaNwLF53vZtUWwboamDlZUDXWzr4m+P1bSrh6TZWu7fVBKAx5ufD8VhW98jrhnV0QzoaWjZDngUAMfA6YmgLm+fBBC/xLNdxdCfluyHQoy41LLjz+a7txJ1TvV55XVg582gy9pRJhl8TiknjUYn/IIMUPOWlqpmVUQDgGLvvxj6vRaDQDkvBDj04RJhMtsI4TQ8CNE2B6geQZdzoFtnZMGzjs2Uz2xlnrhmLDQRNRQiSOKbDSPfDlc+G51VBUBWfNhhtmgeGGn6+DHDf4ouALwhvtEIzChHyY5lH6wxjAX+t4CQbh0UdV+m7dOvjBDwaP1ASDUFNjUV6uzjMSsaipsZg82SA93SAcllRV2Vi3F55bBoVZ8K2rD6YIpexrIC3g9hsN7vmSwT13+WgOqpypISSZ6XGMdEFnhklTvY3zHAkWzYOCcuhdCge0R30HNPbCjLFQ1wPlE6A3CGZ+gnEzLN7abjIhQ+AyBC0GbHND40RlUJpbAUVpMFbChi7wmBBKwLc3wjl5kOWA+8ohYwChs7kONu+HqaUwdYAWSFPGwLrd0FAOKakwxSbIDhvsWpdCbyckAjaED7IMmF8JThuYNuiJaoGl0WhGCJ0iTDpaYJ0AhoBxmYKZVFCLFwlMthVyjtdFO04aiTAVL+lDuMxj8+G7l8IbNeqG7k6FfT3KGf6CYnh3D7jtavn6NtVI2ZUHTgsmZPe/z1hMZdpOhtWDy6V8rTo7Jampyv8pOxtcKQYPf9OlUqQuwbo96ngOHFI8rpoZr1sHwV5l3XDpInhrmR3hNMkpEKR6DEJBi/SsKNt6nVw4SVBZasPjtbOmWvDXNWB3wvo9an/Z6aqeyu2A7FRol1A3M8TmhI8/9kTpqssmu9HBVI/BKr+g0wtWmcSaLOnsgbog2FyCQEyQYof9IbALKHNDYwQ+aoerC4++Bi098MwKFRnbUg956ZCffvR6Bbnw8B3wSg+MdcKCfGjsEVyYYuPRFiWmMzLg4mJIOKDeDvtI8PyjPbhMk+/O9HDnTK20NBpNEjG9kK5ThMlEC6wkcBEl7MaLiWAsGdgxuJ484kjsx4hcHcmuHljR3BexEFDVV/sTjsCWreBrBG8eTJ0A07PgvFKYlAvFaUfva9UWeOVDVedzz9XKrXyoeDxwzz0HU4RDqTMyTcFddzl44YUY7e2Siy82qRht8tOXIOwXhGqhdjucNxe+cQfkZSqh9emnarZjRYUqOK+pgfUbYMkKSWaWoKleEIhJPNk2AjGJEZN43AJPqoEvBLublYjKTFG1UdecrSKCj74HjZ0QikL5pBiv+cPUGRDq8WIv66GjNoul6wSBAgF5gFBdlq04JLphR7rFXI9Jth22+WF2jjpem4Co1f81iMZVJM7rAl9YvR4ItwG39DnEf/1CCEYg7gjj3mDR0O7BsmBUEazuhQ+CwLZ2LE8CGXPxr+t7uHVaNg77STZJ02g0X1wSfvDpFGEy0QIrCbgwmYoKI7VFYGkrBBOCmZmCqiMiGIkENLaB0wF5R/S3S7GBaUA0oTywxmRAbxs8+amyLzDSolgZPpqxcdHYVC4ZPbB4+2CNiuTUNUN9C4wZIF01EBUVQ6u9OpTCQoNHHjmo5OIJyPHCuytg2bPKA+u9JUos/sf/B55cZfaZkXHQbDQ1FRobIDvHJDPPhj8iaes1CPgkbT6YNVGwcrugvg2mF0GhC9p7YUc91LcqN/00N4zOg8xUGFcMOwyLwF6BryuFWLuBTBEYqVECbTYoBJpRoXGHelhOSUfEwmM3mZgGY11K6FgCHKZy6u+Pkiy4cBKs3ad+lgyw3pGYBnS4W1nHXsqmCcZ1lTDe7uJHm1NZ0SnotGzkiShOkQDpIC3VRziWpQWWRqNJHjpFmHS0wEoi/jj8bh/EJbhMeKoOjDKY0ieyLAuefQe29rmGX3sBzJ58cPvRGfC1KRCKw7hMaO6AQD34o0BvguyFLSRcJrGsIK7RMRKJnAGbMce64LGnYGIVpN8+gid9CFIFgRACenslK1ZYxPZZ9OwzCPgN7E6BkLBpE/zP/8ADD6g+e1u3Hmyl4/ereq4ih0FKVgpt1UFCSGVWhYsPfheDggSGAT3FAstvp3KywboNkGaHlDLIz1SzCpvaYd5E2Nhux+iNY7YJYjFBMOBBOA1ESCC3A7OBBNCIqrL3SEIBg9WpsKYeZnnAsKAyE24Ypeqw+kMIuKRKPYbLLhrx4sYpTTaZNTSE6thqnI+VasMZ8VCSlU7caMGV1cHi1FzSPEOPjGo0Gs2gGF5I1SnCZKIFVhJpDEEwAWV9vkiWhE09BwVWezdsq4aKQpX2W7rqcIEVT0BTl7qpf2BAogtSnNC1GWz2OCHpJrQ+hV4p+LXh46MOmFwCt847GAECJeTeeRla2sDaC798FH7w4NGpvvo2SPVAehKsHLp88Me31di3LpA892Scnh5ITwczksBhBywDl1uw8EKIxSR/+lOca681GDXK/KxVTUaGEmDeVNi0y04oPRUmJKBewvoAEAHLgxWV1O6z0xsRzIyYFLhN3C5obIGyQijOhs5eePZDaC83mJvjJtEWpzMEIbuJdBr4S4G9EjZKGAWkAW4wogYpDpiSD5/shs1SpfRGp0LWxBO/Vv2RTSr7aGFbr2BtXSZdkXQ8niAyXTI2rZZ/SZvEZHM0VkxSlKW/Zmo0miRj+SGgU4TJRAusJOI0IdEXbDGEikSlHnKFPS5VdN7jh0AIivIO3/6VbfBpHeR7Vf3Ox7vBCAI+iEs7gWUpiF6JKLNY+2o6k2cqp2/TDzddqkRWQy/8aQOkzYJIC7S0wktLYFQp3HGjJJEAu12wrwl++4ayS/jbm0+8EL66CVq71H6WfmzR2SmpqFCqLzdbcPaMBGPHCsaMEWRmwrp1MZYvjxEICL77XTctbQLDgD27VO9CT6oycSVhqN7O7SEgCISgxwfp6UghiQobu3daVE01lcVDX9+/7hisj0JqN4wuhjbT4JwJDtxBaIhDyIRVuRCeJon0oGqwbAJCYMUNHG6I9EAsBEaKskhIOyJo1B2AJz6GSAy+PL//gvahMo0K0nDzaSjGyu0FdOc4yUyD80Ujo7uy+UvUS3ahqr3TaDSaEUEHxpOKFlhJpMwNszJhdZcqUs+0w4JDevl5PXDHZfDOp5CfDVfNP/heVxDW1kNllhJnAFMr4I3lIEyQ3QaJj5zgBuGSjCo02F4LVgDWbYT5M1Sz4P298F4N7LQg7IFIAKp3w09+keDn/5mgKF/yox/YGDXBxO1QPktHiqu2NvjgA9Xu5qyzjj7PUAhefx3GjlVu8QCVBartj2VBlkcVvR8gK0vVkOXnQ2ZfYXciIcjIgNRUQXMHPPGGEogLz1IO9qFYX5G4EwgATtn3JASRFGgLQYqLcMLC57MhLcmi+UJFylACqyWiitYvyoZne9Xx9aTBVbmwvAdi+yCWC/ZxYRwiSrDGg+y14XUqj66N7XD1BAh1K2PZK48wG9vRCA2dYDdhbTVc3s+1Gio2TNzk4svyk5EFxQHJzbmCH0wvoqYLXt0HqVkosanRaDTJxvSCV6cIk4kWWElECLiuCOZkqZlmhS5Vi3UoY8vU40j8UbW9cYjYKc6DsiLonQx71gBhA9xQ4oYZo+DBq+CZVyA7E7Iz1DYlKdD4LjSuBTqBFDBKJG0NCRosg7oI/PinCd75i8kPbgVbP9mmd95RdVEbNijbhCNbwbS0wIcfQmvrQYGVlQbfvUnVYTU2GqxYliAWU9Gy0lLJli0QiQiCQdWEuajIxsMPm4weLVi3QxCNqcifJw1uvgX+7+NQUgm17UAXkC4AC6W43CDtYBrEQ3E8BSaxuHJpT/WA1wulbrjYhN5OVfSeFoYEkk4DNkfAkRDIBIiUGGnF7Vg+g1C6EyENjBhYGISB8cVwyXTVQzLHe/h1KM1WvlQJC8YWcMLkYHKZx861CxNUtAqqd8HOPfB+PdS1weud8MjFJz6ORqPRHIXlh5BOESYTLbCSjBBQPED/wGORm6KiXh1+9TPNA8EYzJkGs+fBunlgBKDXARcXwl3zVUTm7x5QY0YlfNAJWzeCfx9Ki6QB48BbAEGvQbxBYDklezIl33wyQaU02bsnTE/I4rqLbVx3iareHjVKCayyMnD2Y+9QVgYPPnh0CxkhIB6X7NwZpasrzrp1gvJyg8JCk7//e5NAQFBXB1OnQkmJxfLlFjU1grnnmeyqVSnCCZUqClY5BiZMhp8+Ab09AiJOcKeo4jWHE6QDIhISNiKmSTwuWLEagiGLdI9kykSBLc0gFFP9HO9Mh1+3QsghCTl89BhRMjIduAv3UxapZUd8AsIAmWlBr8BuQoYNlrXA+DQocMOuGhV5TE9V51ucBd+9Uh1v2gn2IwRwYXANXta3wP95EeydUOiBcy+F2k6Y0I/3lkaj0SQNnSJMKlpgnSYICSkxeGYVuJ2qSHtiCdx5Nvjs0NsXPRntgXvLD0a6DhS3v9EKn/ZAcztEBGrKbRoQBXejwJ0q8KVJyEkQmRxmVWGCF/7gomO1gdey8/47EhsWV11icO65MHmy6s3X3yxFw4AJE/o/jzffjLBiRYxJkwxKSy0aGhLccIPJlCkG27dLKipgwgTJT39q4XBAdbVFRYXBfdcfDN0lEpCbCd0++PLl8Mr7gu6ADbO4GLPdR0erDTDAH6c000DEYd9+i1HF0Noi8buhocNC5AvOnib41cdw52yYlgs+2ug0e8h1GpR7o3TGY2wIzCDmsSOFgYwYhG1QH5U4hKAhAI9tg6c2QGO18tr67+/DqL7ej97j6EU4GG9uhWhKgvomk0lFsGh8nIvS6nCWlnLQr16j0WiSiOEFt04RJhMtsE4TXvgIln4K7qgyDvUk4MFzIb/PRDTHAYE4jEpR4qq+GdZsgfIiOGsSNITVOlnjYOVY8GdCPAqOXoj0gq/DxJZqYWZZuHa7qO+O03NunGiNm+6dQYKd8JN/cTBnuovUVMETT0EgAPfefXSkaiAiEcnq1XHKygxMU+ByCUzTYsOGGG1tJm+/LT8TZy6X2r8QAvsRmsE04a6r4O1PIL8X7r0a3Gmwudrg/eVpeKwEO3cncHtdlDpN9tRI1tbA5oBAGODwCHr9krMrwNULKXnwzna4fEGMd2O9lAsX0YBJY9RLW8RO1HTiMsPkFLUy2rePDU0zEXYXHqcg0wGVDni7CVxx6A1ATdNBgTUSTJwQZU1lN/fOyuS6sXbsNVvhmd/CTfcSGHs21S3Q0y1JdUvGlxvDMpHVaDSafpF+iOgUYTLRAusUIeXhxeW76mFsEWzZD74uWDAG8lIPvl/qVtt8vBZWboR122FsOXy6CTLS4IIseLYZLDdMvxQq90FPEHrqoW4JRBxgxARTJkoKpsdZvVEQ22GHoMSyOQl3w6erJLd+Kcyffu+mtlZFkurrhy6w1HlJxBFV85YFe/dKcnNVfdSePfDwwyYrV1rk5wvGjxdH7SMjVXDLper1lv3w6EeqyfLWJsHZ5Tamz7RRkg+fLIPtexKkSjhnjMUliw1kXPL7dwzamgTdrdDTC5MXWLwkQvQ47AQjJk21HtpCkpDhhRQIWHbS3QFmj15NS0oFRnMpbgOme8EuoXAMOJph3gQ4Z6q6NnubVTF88QCtio6XyytsjCeVMZg4AIrLYeEV7E8p5p+fqWH5JsnOPSUYDsElY2I8+w9OUr2D7VWj0WgGQTvAJBUtsEYIfwCq61W6b0z5QTEVteCpZqgJw015MKXvxjhvMry/ASpzYN4kuHnB0bP79tbB6x9CZhrUNqrC8tS+sqQpqfC3LgjH4Ze1kJYPy1dBwAHSCfYQpKQLpmXbkVHI7DYI7zTpiEiwSYh3g3Ty4UduGhotzl9gEAjAuCNmzh0Lp1MwY4adNWtiFBcbRKPQ1SW59loHkYjghRcsuroE550H+fkG11xzdMK/tVXyu99ZlJfDl75kIIRgX6vq75efDjOnq8znjEqwOWDPeLh7isGWnZIrLjK4cbFg6QYILIHGAMQSsN+SeL8eZG8ihhAGzYE4W7dFCWWkq5qDhAHpFo1WAf/d/jCZQROvCYkIrKkGYUBvOvxoMVw2Wh3nm2vhg81gM+D+xVCed9SpHDdODCZxSCFfWga1Uy/jwoc6qd2TRmpJL9NLVrIuPpd30uCjXXDFjOSNr9FozkAML7h0ijCZaIE1AgRD8JvnoaNbzTBbdC5cPFe9Vx+BXUHItsN7nQcF1iUzYWol2G2Qm9H/fgMhJboy02HqWGXueeEcFckCSLerx5UT4HcfQHsnXFgFYx2wdRtk5MNen0Gk3Ul2NIE/HsFvsxExJaR5IWLDSgj++EeL3//OwLJgdyMUyKGbkY6a4OTNFSb1m2NMGSW55RYnEyaoj1lRkSAWUy1tfvM0TBkH82Yevn1np3rE4ypKZLPBqDxYvgsau8DphlvPg6XLYNMeFUVavEBQNk4wZgxsr4N318PFs+B/ngNfQNLllyx9TlD5dYk/6qAuHiLqcEC3AEffDIGAAe4ENikZbRrEYoKGZmUSawhIN+C5jyHYAQsmQHOfCaw/rPywyofzATmE5jZl3+Ed4Pr2NjRgd7t56Ode9jVnQgX0OF3sKHZBSGClm7wVgQsT4NHfPjUazfEi/RDVKcJkogXWCNDQAl29UFEMsRis2HhQYOXZIcsOnTFYdIhppBBQNEgqblQp5GRCXRMU5sKPrlc2DkcyuxQKLoU/xSEag4vPh5w81cKnOgK+dsgXFqaUTBsDTdU29ncIcNhITZWUFKvI0p4m+MWrMGss3D1Ee4A3PhSMG2ens9vOPfdC7iHps9xcQWMLvPQOZGXAa+9BcQFUHFLPNG4c3HuvQWYmhMOCTduhshTuXgB1HTAmH+IhaGiFs8ZDTwBa22DeDNjrgSfeh96QmkkZCFlIE2JB2PWOk54rfMRcEsNuEM8zYT/gR4mssICQiTdHckEx7K6GGj9Uo8w9c01YuV/ZYNR1wq2z4Y9L1azCslwGJJHof6IAQHcv/OJJGFcBd1/X/zr1K1cS9+Swcf98FW0LqOVB6QETxttNvBmqTZMWWBqN5kSQehZhUtECawRITVF1R/6AKoouzlceTz0W2A14pBQCCSW0hrvfB26Dlg7ISFW1VwNRlgd/e5sSWMvWwW43TJ8At2TBj38O0mNj2lSD3AyDCqdgfJGN9m6LG68X3HunQSyuxOG4Ipg+avBjS1jQ3APlJbBlJ+Rk0W9dUDwOCJU6lbLvNSCR+OnAaXiYPFl5Hrz8Bjz5V+iJwk9+cLDHX2uHmsnY1AZjiuHh22CLVDMpW6PQFoN2v2ovKAEskDbo8Tswqw1otuEqDROuNEnE7OqXEwV7zMThkQhT0tsuSIuC2Q5NfuX+7nEoQdcTUOfqlyqC9fQK+NrCoz3FIhH47z/CgnNgdj8mpF4PzD8bSo9hvzDhmmtYucfAihrqIsdQvmDbbFRMNbh8LoxOgewB+iNqNBrNkDC84NApwmSiBdYIUJALt14OH6yCMWUqgvRoN+ztMxNdlALnH6cjt9ulolare2BHg2rPs6oFXl8HXhN+ej5c2Jev8rjU49K5MLFSFWT/8nGoGge1TYLGVpPSPHB7YWI+XHiBQd50+OV6qG6A9ChkOg+KoGPx4jpYVwu5Xrj/VhXZOXR2m5Twl6UqsnfuWUqEzTsbRvWZrvbQzE4+woWXKi4jFDSwErC/A0ZVwpINMHs89NKLPTvBV2/IZEM1jClRY71UC7vDEMmCYC/ExklMe5z4PhOQiAsjxLc5oMlAChuiM0Z6ThcZ47vpCWdBCjjjqaR5XTQQpbcwxrl5NlZ+7CIRF7idICKwrQHG5sEzKyEjBXJSoa4dugKQe4TgtdvhrClQ2k+UEVT687JB/p8ZNhspbjWbNBoyaAuBLQrzR8G4DLjQgEUlyjtNo9FojhvpRyZ0ijCZaIE1QlSNVw+AJX7YG4Fyh0rTve2HMQ4oPk5Lo+Xd8FobpJvwbjds2AaJFtUs+r7XYeltUNnXkqaXEPX2DjxlTqzWbCQG0ydCSQE0tUB7M2RmqRqgaefAf34Iowvg4w7ocUNFNqzYBjMHKXavboNUN7QHVGsczxFmq/E4bNqtCvKvugOuPiLlaMOOgUmox8vONsFLL0JvD0yrhMwJcN5k8ONnFZ9ikSAcO4dV0QzW7oPbUlREcGMD2GLqedQnEcUSMSaOtANeQWyrHZlmYdotHI44rliMc6pW4Awn2Oa7AFsiHSdRSgr8uFIMtvbGyQ16mBJIp6ZH0uCD8fmCWArUxsHvV+lIlxsilqrFau6F7c0wtRjG5MFF8zlhHOlww6Xw1lKY5VDF/fOmQUePakDt0GF9jUZzgkgBli4zSCpaYJ0EWuOQ2ncTtPW1w/FZx7+/9b1Q4FRizW5ATKjImLQgkoDVTUpghYjyAduIkyBOgvGZEfKyS2hoVtEluyGRUVXak5UteOwNWLsNElOgLQE1HRAIw9fmDH5MN8yAJdvhgnGQ3o+rud0OX7sBgmEo6KfWzEsOGfuv4g9P2WloE2zfApddANl++IfbVLsef9+6loQP99oZnarc7pfsg/d6wL8TIkGIRS3ifqlyhDYTigykzY6ZFyMju5PUom68Th/phd3YhZdss4EUr48oPXQbCbYLgcjuJTerF3++ZNtHFWxuz8GyDPbXGjhcgspsKC5TGTsjDH/5nerRWFcN7l7ImAC3XwB3TIfJJzDDMG7Bkm5YMFcZv3YHYEohtHco0TtuBP24NBrNmYPAi7DpFGEy0QLrJDDGAZsikCJUdxcDyDuBK59hg9owpNrUt44sL+AGIwUcXnh1P3QZcMnoMDF7gmy8hInRYe/mnhtL+HgN+AKQZbMINoK/GxKlJqtXQH4u7GhWVhDnZIAlIG8ILVrG5KvHsUjPAHei//ficfjP55ysq4bUdOgFnl8GCy6GMOABvHiZxWwSIsGuFA/Nfmhohy27YfV+kGEgYKl2hVEBGXYYBaSCmRmjYuwuUlJ9pDgCRB0OEnaDkJVGty2CVwZpj0RImNCaCOEUXeQablo7vGzanU2o3VCF8F5JSAh2BGHXfpWitTohEYZQDyQyIJ6jlrX64dmt8N00SD9Ox3ebAfeWwDuboCuk0pJ7OuF7l0NtE3T2qIkPGo1GcyJI/CQsnSJMJlpgnQRmusFvwadhcAu4JwPSzCAdbMHERTqTEQM4vEXj8GmdinrNLgO7CZfnwh8boCMKBTbIKoNmCcEoOG0wqwhq/ZIl3QHacjux6CAHFxcwjrRUuPxCte9lywQ11RaNXYJd1cro1OWGi6+Dd6uhPBPqeiD9OHorHoovAKu2wIu7ILMIvnkOZHskz0ZjtFiSL9kc/O0zgsc3ogq4W8ElYNJC2F0OP1sJfzcf3HZIJx1fBFJN+N1q2L4MEgLIAnr7xJXVt5+zAJd6nWFvI2bYCMY8hAMe3O4wZoakXthxI7EbNvZHUgnEBRXORkJSEAhBzepiIiFThQlTUIMFlN8YLhB2CEbAgUrVhUIgXeq90TnKfT8Uh/T+rktI1aYN1scwxQYZHojEoSsIRRnwygewarOKDD5wS/9RQY1GoxkOlqHrDZKJFlgnAUPAQq96HKCFT/CzC4mFgYM0+m/u91E1vLNLzYaLW3D+aNUS55vl0BWDFBM6E9A4LkowGmFJtYuA6KXL48N0d1FFGb0ECJDAw+HT+qafZzFmkuCRvzPYsQNmTFYzDeePiVHdton6thjnjq1iWuHACmDLHmjrgnOr6LdlSzwO3/xn2LEXfDaYfA7Y5kIQ2JawiEj4zd4oT9oFVJmwuk/AFMKOgMFMKWkMCla1xJia3Ya59U3+fet0Ht19Nm2rIdEiYbKaBUgYJYI6gUIgAmZrlExvJ5Vl+8hwdBCMptAUKKKn242tI4a3opd4ppcQJu0RD5Xe7WQm2gjH3XQ05YAlMYJgGahfgiFUO8AEEFCNnwOWmuDn9IBhUzVSo0vBH4MJOZA7wOX7w1K13XeuHvDyfsZ5Y/pcGiIwdyz8/nnIzVIzStu7Dgqs5m547CNlyvqlecpXTaPRaAZFpGIYyUoRPpGk/Xy+0f9+TxEWMQQmEgvJwNP0YpayJJBSCawDOA1VhwXgssXZ4dxAEB9jLD/bmwpx5XSS6eplT6SCDiS9hkW77OBrtlSKDYP1+PlQ9JKSbXDVDTl88JaNs6fBtZdDyLaWKWNWMSZsMqWyHTtX9ntsnT3wzFsQiSqvpwX9uInv2Qc79kBliTLVzPfDU38Av18w7xob7WMi/CwSRThdCGkgz5YQNsAG8TQ/Xe5eUgrsPNqUYG7qNgr2bSWxN0TXp9OJ75equC0ChFCiJxXlFSWBnRLTHiMgvexpH0Nacx5nn7MaT3qIHW2TsFlxAr1eomkRHCJKtmxgkWMJLZFcWowC4tEowRh4vHGCERvxhFAqJw0wwGXC1CxwdkJbL6TaATfMKoO5pXBjFZSmgznAl8KFU1SwbSjYbXD+IRr88vnwwjswtkyJuc+udwu0+aAzoB75/YXONBqN5ggkfuIsP9WH8YVCC6xTRA7z6MKJiZtUxg+43vmjVJTDEDCvov914iSIEEXSRHlOGwtzHCy34nwQiRKUW9gvS3HZoviJ8IdIDl9xSV4TDUjAh4sbLoly5yUHPwrtBCgtdGLgIoFvwGPzuFStVlcv5A1QB5SXAzkZsK9BnYNLQlsbpKfD+pds5P+dHyNhx/KZSAuMFIkVBdOmDLM6eh3sm9iMtz2TDjOH1/ZfzVt/mk20UwJ90aRWYAzqOSgRFP3/2fvvMDmu80wfvk9VdXXOk3MCBjknZoI5iRQlKpCikmXJtiQHeT+t7V3vep3XYeX12vvzWrZky0pUYhSjmEECRM55BpNz7hyq6nx/nKEAkoNAMAAk+76uurq7usLp6u6Zp8/7vs8LZAWFaT/kIdvvJZ/wcsi3hNUbttPtasLChaZJQEMIaDePkLQCdCbnUQgZxOLjTBjVFDwakZiNzLhIF0FDudxHg7CqGlIDMDIMRgiiPmgMwseWQtPsNXEcONKlnPgXt56ssFx2mvfzXFjUCn/0G29cv6QOTowoy4jy4BufL1GiRInT4Wglv5e3k5LAukC4CFHBNWfdzmfCbYvOvI0XN2tZSB9TeGbnRJycTloUVUxdOmQdkxGnyJAcooFxApgcR0MjTRY3/baH/5YostMu0qqv5A+CCaqMMbrzGX6Y+yb7kzeyQdTz6UoN/+ynxuOGr35CzWCFT/PPPBaFv/tDeHkntDRCYgw2bYLpGYkvKnFJSX1dnl3HDRAajgU44KDhNosQTNMxrXGjHsDV5eHhbywFS0AdkJMwKmFSqLBgI0pcNQMCSKKal44A4zqZY36mmmOkFwfwuzKkzCBayEYXFkKCo+tIS2AbGjnbi0vqeOMeiqM6jrQJexwKQmA6GoYDUocXDqo8qJsXQt843LoQvngpVJ/iifXKPnjwWTWTtfMQ/PrHz/q2nzcRP3zm7ZrlL1GixAcGQQCDy9+mo/3b23Sc9zYlgXWRk7JgLK8K4qJncOuuJo6flXTyKN0cxNYd6oo5juTbybs9FC0DzcgwaFtsKaZYbmZYR4xyIvTIQf456ecZq0BRCAYtg0LiKv6nr4OXCi8AXpoCr3B/sgIx4OFLDeKXjajdpsott53Th8KizTmurpX093sZK4BnnkOnJ0/1NRZRx2A8Nkh0QZ7pdBRnyAQdhGbj9udxV6TIjrvorzzEwOPlEI5CHCWchIAaCQdmT7QKyNnQm1UZ/y1hqNNPhg+nNVJDAbSgjScOultgeot4jCzIIES8eHLdtJkn6JFtJCbnM68Fkq40vcdceP02LY5BRjMQLojZEEzDzUtUAn5vDK6b/1pxBdA9oFz3YyHoG1Z5acYp37zpFBzoBa+pfL9e7whfokSJEu80DmkKbLnQw3hfURJYFzGjOfiXbsjaKrz2uUZomcMBvnMSHjgCUyN1hKpriDTuJBjSKNohRvNVIMBvZihIg9y0m0OmSYUzQTlH8RMlQQhhPs0a06an2MaA1cCA4/BScZiiO4lPTJLJ1GKYRfZNCzK255ezWIem4f8dgw83wLVz2DmMkOVhp4fdw5A5Wk3n0TC9ZUWC8y2+GNLolAWkPsnaeYfZl1hOIhhB5hw87jwuT4HMWIDAgiTpQIr2hbvwhT5DJutXIUAHKBMQkcpPwgW4JSwzIWXAcE5N6YRRJloCREanzKeTDIFpJFkpsiwUWXpIMmqUEfFcx2Km2W356E26KffY5BYKllTAZJebdLeLWjeUl8ORQbAN5ahfNRsObIq98RqsWwpHupW4unTFa8VVJg///CQkMsootmcUPnLpeX9kzpuphBKC1eWlisQSJT6o2JSqCE+HEOJyYJ6U8t+EEOVAQErZdaZ9SgLrIuaVSZXk3uCD6SI8NQK//rq+gNki/O1m5SC+8yVoWTmfWsdBCg3ZFKVvZj6ezBSGmWMyH6eQ8pCJDrLN5aGdUWztBHkChLUaJqwAza7jDBWqaBY9TIkDJBwXGQ3y7m7yuQFGHB8TWgA/cQo2PHwcjg2Dc5p2MBksxrOS8TRMZAuMpsETE4yk4MUBSUNzHssBj7tI08pOUuNB0qNBnKLAHcvir8iQMfzkLQ2nTNBY381ha7H65E6hyhFdAsqAYVSIsFyDMh3iLpjml7lZrrjNkiaL3zFv5UFzHI0pwozSTAUuchh0EkGSp4o7nCA/tnW0gs5yl4dCwKQ5BEcHYMinks5bY9ASh3XzYCwNqxvg5e0wk4JP3azaGoFql/SfPqNCqeWvE2DjCUhlobFcNYbe231mgXVwTFlxtL1F76vdh1S4cuk8WL4A/vknMJME0wW/9SmIR97a8UuUKPHeQiKQJYE1J0KIPwLWAO2o+KcL+B5w2Zn2KwmsixiXplzLQVUQvr4lStGGb++AQ2NwZBKmEzC9r5X+SR2jIsuoqw6jSmdotA63kUFKDbc7g645OLbGzqlF9AeitHi6celdrNYKTBVjBPT5fNX1BD/xGBRyLhJ2EN2xcSezLCtLk9UA4iQLkMjD0ojygTo8CT/thLgH7m2HkAn1+KlPxdk5ZJMbdVM0MngnBLrjwoo63OoIXpEW/VqVqswry+CryqgqQCmxpIHuOLiQhOLT2C3AUVTlYBxlpe4DalA2DYah8rEMByKaCiUmQE/AihWCy6vi1LgdQiQ5QYJ6orjx0IwbbJ2e/BCidxGPPh/GrQlYDIUGWOCBrgPQ0QMeD/z6bbBoiQrr/XwHHB+C7n6Y7oeuUegrwIfWwZpm9V6dLkct6ldibWQasgVYVD/3dgCjafj3/cp89A8vBf95Nngem4SfPgXhADz4jBKCiTQ01kLPoJrNKgmsEiU+WGj4MbnkbTra/3ubjnPRcCfKWXEXgJRyUAhx1jKiksC6iLksDkeT0JcBrw43v84pfSQJ+3thSQh2jSsvTHvcYMhVS/vKvcT8I4S90/SVVWE6Frpu4zdTuJ08+QEPvSda2a+1c/O6Z4h7Jok5XWx0unF7Q+iYTBPEbybxWhkGcnVUxseIx2YooqZP4l64sw1GMrCmCv7vfvC7oD8Nu8fgqlow0LjWU8GjQ0lShRTBoIuxlInR4+GrVwq2HqrAH93DZHUAW2ogdNxWAd2wsDHI2H78Tp5WYwxfOE9PpEmF/KZRiexxVHK7AVgoYWY6+LQ0ZqxIMh3CszpDS7OLVaaXKxbAQXeWBC4EEXZRpB4HkRec6PSTQZLZF+HAgKr2i7wIX7oN5jXCozXQtgh6JTw2At0eWNUAB/phXhUc6oc+C/qKMLMP9vfA//clqIqc/j0O+uBXr4ctR1Uvx8vPUNAQ8cCKSvAaKufrfHEcZfvhMtQ1DPlhzSLYcRDa6qHhHJz7S5Qo8f7CIU2WrRd6GBcrBSmlFEJIACHEHMk6b6QksC5iQi74aqsKDwYN1ZblVPrHYM9ByObB1CHVCIxAKDqJ28oTtUaxHINy/zgzVohy9xCulM3UYBmd3e3kpn2QgP54LfGFkzi2TsIqMOTqJOC6nPmFw2zR5zHhhPF5NG7zJxGOwTbnBHWiiYius64apLRxnFeocFscnKoDrYGYx4WFTRfDJMNJGtf2seX5dmYSHhwN5l0+RmfjDI893M7Ag0up/fwBchVeipZOWgZw8gJdk8S1NJdonVzpKfCD4t3YTbNJ67UoQTWFSmAXs4sDFDUyYwE8DSM0NHeRSgbxrkwwFbXJxMMcxk0ZBlGiHGCQSSS9fZK8MUNZthWjEsYnoXsEDk/DfzwBjWXwuTvgSAHGR+GwBdsPwg+OwMyUanadyiix0j8ImSx4DNi0AT52JUxOw6btKpfuqvUQOuW3T00cPnoOeVemDp9a/NY/V5VlcNtVSlBdf6mauWqqU95abpNfFjCUKFHig4NEVW+XmJMfCyH+GYgIIb4I/ArwL2fbqSSwLnIMDcrmcEgHqIw4zK922N+v4S3TqE5DrA3w2xRm3CxYtQcjIBkpVBEgTJPRzRNDN5JKxnGEoWaCNDh8bAmV84dpTPeQznnxdY4h6l9gcaSG9cVnycpmjvnDFGSEzdkQKT3HS5kJ/qawnXj+BE7AwAn28NGWShZMHiTormJh9E62cYwhJpiSeXbX6cQvGyN7CDx6jmJNju9N2Iymi/TvrmEq6aPl2iO4l+WxA5IIfj4dKOdGEeMQizlBlvmaF5c0sFwOFDSVb/Wqw7oze/vq3wdTMDlSheG1qKkbobylSNHUeF4UWUqMBB5M/FRTiZbrZyxrU27Pw5xpRQi4ZBE0VcBT22BagjEBOwbhRAb2TEIgBfMrwbFgsAsGBBgeWBCCTBLyXSq8e2g/OJfDd34G00k1c9Q3BF/+9Nzv6fAwnOiCDeuVwew7xaWr1HIqcznxlyhR4oOBRgAPG96mo/3j23SciwMp5d8KIa5HtcltB/67lPIXZ9uvJLDeo2Qosr+8kys+a3Gb46avP8Kzhz2YFoQX7EEyQrlvDFuXlHtGSRZCVHt6MeYV+OnBu6HKojDqAVOQtX10jLUy4K/iN7u+heaWLDj2Mscu+zzzzBXkRIg8bnYWIWGAXvTSKv4Pu9LHWMxqqsZ+gfBchc/tZ20lSGcXRXEdw0wSI8TPJ11s7omR+k4Ekjo4kuFDGfSNFnrIRvNKEtMh9vxkHTwM0VbBXTp86HOCshiAxk8HbQZH3Pg9AisisGyJzAqVY6Whbl2oWSyJcnTXJVO5OHXRBEUjh2F5GJIOXlngE2aQSZFjFfXY2Va2d4A7CqmUSkYPBlT4Ll2A7R2wpgWePwQdY2pmyhOEwzbMHIHcDAQqlXganwZ7CPQZCJdBYkAdb3wKGmpOCizHmVtA7dmjfMIWLYRI5F35KJUoUaLEbIhw24UexkXLrKA6q6g6lZLAeo/SyzQJ8jT6/PRwkHmtGSL+LK901WLYOm5XlkrPMKmCH9OxaDGOY2oFgsEMY/OrOTC9lOF8HbKoUe6MUscQlcFhRABakycYCZbzrel1/CIxwcqKfeR9ZYwT4XihmVrnOCFjmJxvivuOneDO7FFCvgSBmtUUZS0uXBh4MHExmnF4MhUjfV8YHJeyUbA1Cgf9+NumybhtfFcX0fdrOIYg0GxzlaazJKwTnI1y+4sm4+M+vIECtRGDqNsmqwlSfRpJqWEHhZqNM1C9CE2gKNFri2Bo5L0epgoGmijilSa9eZNniyO0+Kc4ZuVZ5W1CSjjaAYePqhCZ4YKyavD54LKFsKgGnjgOC8shakOHCdkjgKW2L05BvAqWBGBUgB5UvmUbVqkk8uULYfcBQKiZo9PNTm3cCKtWlcRViRIl3n1KNg1zI4RIon66g/oP4wLSUsrQ6fcqCaz3LF5c2EjSFLCdYRYMHmF1Zogr4zrHqm9gNDRIQbco17vwigw+0oxQhU9kudS3CRud6ck4nnCKS9tfojnWTaU9xvSSKNFsivty9zBWgOFkFQ91r+aWxc9SHu8hbpicKDawlyX4Cwnu8j+AbIMRe4y0tYecfoQO/b9xs9Bplyn+9EiBGU8NsqAr5/UJARUAgsKYiSsE4QUJ2tY53FzvQkSz3GxFWWh4f+kX5dEECzUfJyyJy2vh13UWLyiy/UUP1iRk4hIuFTgO/LKftSORSCKGxWW6n+05jUozjy4gYgfpKhbpH6sikfFzrR8WV8P/eRYaKlUhYioNu/apKsnjBZgeA8OnEsyvq4WePki4wFWtKgT1cVhUB8kOiMRAd8PVl8KH71DDufMGGE3A8T4or3zj+/kqbjdUVLxzn5sSJUqUmAuBHy/rL/QwLkqklL/MmhVCCOAOOHs8tSSw3qPUE2Yl1QyRZGkhjjvTR8ZXQUXOwGWlmdYr0J0QfvxonEBHQ0oNG50J4rSYJ9hsXMHG8LN8xvoh2ozFQKyaiJ6gM9DImAwzPRNldKYK2zZ49MhGvr7ur1ku0vQXqtnFGrx6niVVh8h6faRkgHw6zMKxHA3uX9BdfZjfe7adB7ZcA+uz4HOgqEHFrCkoEiISa8iDJ6qRK5smg03cgGrDeM0H063DF5o1Hhvys6CswKaBIn37waVbtK6QDHS7MQNgmxrjebAzQBFEj4tiwOBl4SYQhWJc4pY6WUNnnhcOph3W+gN0pOH2GmiIQyKnZqQsCzJpKI+oGaiuQQjUwpEhldC+rAISPqhwg9sC04QyCU4EnCqYmFA9q5NpiEVgfAYGJ6G1AR57GTYsVa+tUIR/fxIKFnzhZvCW8qBKlChxAXDIkGb7hR7GRY+UUgIPznpj/f6Zti0JrPcoGoJlVLKMShyjgpy+A5G1cDsCr3sDxgwMOh0g5lMWrsSn5TGZZNL24RJFBu0IhlXkF9xMb7aJJYE9VIkh+mnF73jJOS5q7X7GrEo0LArSDZrDemsbz7CR/lw9m5wruNb7LKargFPQqTvaRVViioyW53d6VvHzlzbgOAY864dFRThkw5Su+uqsKiJHwS66cKddzDumYfVZ3HGzSRoLB0kFJ42emvzw5TaNnmkPmx7wMDXuoCctIiMaq+/SGagHnw37jsFoFPIpjcJBmN4HiUZo2ihwtQpML8QN+HIkSkFXFhMBHdrKYXULTKVA05VLe2sD1MXBpYPPBXoMVrfBsRG4dz2sH4QndkF+HK5cpPKrGhfA80MwrxU8ARiZUAIrEoB4GHpGIBCGH78EtXHw6PAfT6qE+A0LYM2CC/eZej2OA7tPwGQKVrdCrNQ8ukSJ9zWlKsK5EUJ85JSHGsp0NHe2/UoC632AZoTwNf4uMrGfne4M3YECO/uaafa4mZRj+Ashkp4MGRIs1A9RSLt5PLeQYHwG2zEYclVS6S5n18xq0rqbqnACTStg6kXc5Mg6frzlU7hlEQw3C+VBMokQRUz+y+G/4POL/42a8AD1xUGy5T7+P+0mtm9ehcwza/SpwUFThQbrgYKAaReWqeOJQJ0pWDvlZewQ7Lx5lH5yCATXE2cBJ+1Gchb8+x71jz9YKNAzliDsF1RURHEZBnuGICHALEBqF3BCVRo6x2FQQKWAD10C24rwYAqWVkKNJhnzZ9nqknzqDi9Pv6SxvweEFxY2ws5jsLYBFiyCplb44VOqHc5wF0wcgfJRKKuFhgqlG/vG4TP3wLNboKEKGmcd7seT4ItCJgHbOuFftwAmbFwA9WWAvPgEzN5u+PFmMA3Y1wNf+9A7W9lYokSJC4eGHz9rL/QwLlY+dMp9C+hGhQnPSElgvV9wV+CUb6SPnVgUmRfK0zW2mKAB18fBZpQDbKaMFE3laVyZH7LFWY2FQaU5TBE3fdONaHmNRMTHymA/SRPqjAgJGWRlbA8Vugu/XknILFJb1s/kaIxj4wv4r8/+T8oio/zRov9Fiz7NoVQrSTuEndIhiqrsmxGE/FOkc14cDKTLALdGXRFungHDEjhei0EK1OIhicVhUq8RWHkLCjZcthSe67eojkqWlkk8aZvRnQaBcQj0Q7ANphyQ7bM7DoCYgbE++FYMwo3QDGzNQ7XbYcrI4gAtERefuc3kpUPw6A7ITIJIQm0IPncL7N4PNRbM9MPPTsCVa1QI8KXtoDvg8kLKBZuGQKuDeYtOtst5crcyIn38sMrrShfBLsCeEfjmx6EsBC217+5H5mxMppQZaXUUBiZV5wB3SWCVKPG+xCZNkp0XehgXJVLKz5/PfiWB9T5CR+MK2pkgRWOknKRfhb+8OgwhsAkySS2VHOVO3yRrnS1MECHtBNiW3kAh46XO30te+CjT0phejQ2evSAt1ogeKjQPS5wbuC8dITXuY2bUA4MaRcfNuFPNj8buYEbEmXLHsHxubN2lWtkUAR3SM0E8rgxZS0dKKPPD1TENn4ThCVi2SCOPzhB5LCSLZIBEGnwelXgeMKEQhucnoOImH7cMOaxq0KhpNikch8aV8FQBtuTBDDhYuoNw24gQVBRM6hYIOgy41gSZVC0MN/dqtNR4aV5UpFooJ9cljfDDJ2HXXmitg54h+MXLUBVTRqGgZnIyGeg4Brqtqg8D1dC4CBpiKuT33BForVCPF9VD7xjkhTIMzWYADUQeVrSp13gmJjPwYhfUhWFN3Tv5KTrJqhbY26Vyx25cAe634B5fokSJix3xroUIhRAe4EXAjdIhP5VS/pEQohm4D9WjYyfwaSllQQjhBv4DWA1MAJ+QUnbPHusPgC+gLKd/S0r55Oz6m4C/R8VR/lVK+T9n1895jtOM8x84WT34BqSUv3Wm11kSWO8zyghRRggEeGZTmLLk2MsBPPhIsw6LFqJswRQCyxZ0Zto4kliEcBVZXrmbGbucyvQMlXoM6fFj62mqWYfExY5clN6+SnITQfr3hMASUC4xXEUmtAjRwDjDrgh5n4aryaHYq0EIOAR2pUHaFwINKnVYKgTtQdXkOJuDS9doRKjgoRNZOo+b/PUmk8ETUF8F3/g9sEOgB+C2IIwUNe69JkR6Bg52w3gKzDGobpB4/DZuO4dMS8qDYzheHZEvcuxEG9YC+P4mCOrgTUN+VJCO+AjasLUWro5CxA8bmpXjQ2cRDuRhZC/862/CiRnYPQrZGXhyF6Qz8NFrIRaGJw8rjywhQBeg63B4AH64CfJFJdDWLYPjXSrP3++FO646u7gCeOIYHBiBbf3QFFXi9J0mGoDf+RBYtmoCXaJEifcvGj4CrHm3TpcHrpFSpoQQLuAlIcTjwO8CfyelvE8I8f9QwumfZm+npJRtQohPAn8FfEIIsQj4JLAY1ZH2aSHE/Nlz/F/geqAf2C6EeFhKeWh237nOMRc73sqLLAmsDwBFLBzAjYmNQ4YFLOQOJsQmOrS9TPks5rn3c4UxQsbxUCEG6S2G0ZIWi4RDsLKWpJam2qnlyeQUphNnasCAtIBKh+pIH4U6D4OpanpkC/gkrqYC6BK3YZEb8WBVgOgDXxksqBXEfYL2CGgF6BqBDRugtgb6xgz2bg5ycBRe6lZtBo91wY+fgM/cDaaAnICwCXtOwKYjStQ45SA84Cy1cB/PMzPtIVBMUEi78egZYuUT7DrRgsfSkGUQtiEF5IowLqHoguemIOPAh8shVg1P74Q0EHWUgHrkMOzPQXU1NNeDywUduyDgU2aiERMyRUjlYHhaVSS+eAgqQ6qp8/A0rK+Humo1Exb2whdWqvdoLuNRKdWiaVAVhP0jEHarhPt3C017Y5PxEiVKvP9wyJBg97tyrtlKvNTsQ9fsIoFrgHtm138H+B8o8XPH7H2AnwL/eIpdwn1SyjzQJYToANbNbtchpTwBIIS4D7hDCHH4DOeYa5zfeSuvsySw3sdIJMP0M80UUQJMMI2Jizaa0PAQo4KwsFlSPMyMHiTizDAxFaNjYgH5GTdFzWTEMmnKwYK4xUhqmLylESXE+Igf8hCoTRBqm2ZsuApHd2HpBtICqQuC87O0NcDSXAG/HaGjG/ZuByMDdR4IZgAvLF0CW15RIajGxdCXhgNJyIVhKA1mHwyPQtyEX6mHjgy0eeFbv4DGGBg6VIVhYApyXknC1sFvIx/WqLxlCLOqwHhPOYTBOi5x1QlmglAvwLUSblumcqCKDhxIwVUB2J6EulroHAPbC2YEtvWq83lmBc7Khaov4f4T6vy/cQcMFOBPf6JmttqrYdoLx0bVsU0dbozBPZfBTB6qA1Dhh/2H4ac/h1+5Gxpnw3/ZHHzrPpXj9aufhKubYX4ZhD3gM0/zhpcoUaLEeSIROLxtjUjLhBCnzv58U0r5zVM3EELoqBBdG2q2qROYllJas5v0o7rOMnvbByCltIQQM6gQXy3wyimHPXWfvtetXz+7z+nOcVqEEOXA7wGLgF/GHKSU15xpv5LAeh8zxQQH2UuWNJ1kiNNMO7VEUOaziXwX9V1HsMOTFMt1tLSDs89FY3M3hWqTdCZA0h0iP2jR9QvBwnlHSE81Y8sUuoxh6RCpnwRHEPJNMxWIU0gY2EU34FDMeqirmOSKjf3cRYDhMYPHm6HzBETicEkbXLUYtu+AfQfUmJvKwSqClYOwD3wWzG8BfXY2p8mnFtt54+u1JThTGkMFHYp50ntCdIwtwFhUJBkJQBM4AQeXpuOagvUFCC8Fa/brMmFBrRsGZsBy4IZlsLMX+maUxYLbdVJcgZrdWbgCrmmGS5tVL7/OJ0EfVSHQ3oPgaga/D0IeGEvCWAYawycbKk8n4UAXzGSU6BpPQ8iEsQnoG1Thuf4hKI+r/KsSJUqUeCfQ8RFi1dk3PDfGpZRnjDdKKW1ghRAiAjwAXEQmNW/g+8CPgFuBXwc+C4ydbaeSwHofY2ORZYpBpphCEGOabvzMp5oIPmKPbsJ/Yj+uQIbAiimW7juGmSpQGDXZtnYlB2KL6R+vYTAdp1hXy1iynf5xh3nJvZSXVdKfdmOaBWy/hqcpiz5axDluIEQRLSmxR3V+fjhEfEU/wVyKb3w7wpbjYI2AzIIMSfBDLCS4YkEeO5Li5USG3DwTZypEIGgwv1qn0efwypTNP2YtPuHxUKHp6JqyOHjygBI9uSK4w/DodgPHsiHogiZJtsenvgYxIAqBRof1tTo1OnymUZIWkk3jGt02VJlwZzlMJZSAc+lwSQs0JmBFNfRNwUxWhfZACT5bQkvFyUbJg8NgFmHfKyo97fL5sKgJUlmIBOGJo+B5Ci5tgpgfvv8k7BmEY0V48QEVMo344ZOLYf1q1Uy6vfXCfH5KlCjxwcEmwzR73vXzSimnhRDPAZcAESGEMTvDVAcMzG42gDL56RdCGKjmaBOnrH+VU/eZa/3EGc5xJuJSym8JIX5bSvkC8IIQ4qyurO+YwDpDlcC1wN+gzLpSwOeklB3v1Dg+iJygwBEKzCdMhCijTBEgTIo8PsCFTpbDuMf2kIkUiXZNErYmydWbaAttinmT6N4kmXIfcXsCTWp4vaPko34G0/NI9waZCObAb2BP6+hBC3SJN5gkWYjhjuZBh0LKhWXCs8c0vn3YIL+4iLZUonfYOFt17KKBFrWx102ye+00O/M69oDACdjk8i4sYGvew/OdLoKXFBgpFNjmFPi3QAQDwcZ2qAnD4DSE/fDfN8PY5gJUGbBchztseFKHIVQlIwVcviLgIu9y+O9DFpmMYKEm+WiNzk2znlWEYFkt7BtUyepRL2xshakMfHs7JAsq3JfKw8paaIicvPaLWuHBx1RLHduGgBuqIjBRbvPtE5K8JTjyuM4l86BnHA7uA7xABFzjUBaHrB8OD8HyevjMje/ax+ZtwbbhiV/A6DjcfjPE4xd6RCVKlDgXVIhQf1fONRtyK86KKy8qGf2vgOeAu1BVfp8FHprd5eHZx1tmn39WSimFEA8DPxBCfAOV5D4P2IYyB5o3WzE4gEqEv2d2n9Od40wUZ2+HhBC3AoOon+1n5J2cwTpdlcA/AXdIKQ8LIb4M/CHwuXdwHB8okjj8hBQmgv0U+DxX4cdNNzP4aGA58/DjZpjnGLppPoFXRjDDgslFUWriw5jDaSzNoTzWy/r0Zrp6WsmICIfLlxDP9lHttclPeSlU+PC1p5kZCVJZmcFJaLjDOcxwHicvEKaDXmvjKuZhXEMOSXQ7T8X6UbwfTuAsd1Ho9iJrwWwsUJwyEGVgRvPYWRfanTNkNwWQVhatycZu0PBKSbctmZBFKoWJELCgWi2TOTjSXUCTRZxuQ6VLBiXG55NYgyakdYgbTAyYvDgiiZRJXKZGTRBMj2T7ONxUAw8kYWcOfJXwsVpl41UdVLNkYQ/81uWwdxCSeWiNQ+80/OULs/lV8+DaDarNzg/vh/mNcM+n4Pu7JQ/mbGYmBXm3hJzgsYJEhAUs1OAEYEDRUk7yyyuhLgbHhuZOfr+Y6euHTVvUmF/eCrffcqFHVKJEiXNBx0uYFe/W6aqB78zmYWnAj6WUPxdCHALuE0L8GbAb+Nbs9t8CvjubxD6JEkxIKQ8KIX4MHEIZgH5lNvSIEOKrwJMom4ZvSykPzh7r905zjjPxZ0KIMPCfgH9A1cZ/7Ww7vWMC6wxVAnJ2cKCm+QbfqTF8EHGQOKiLnQcMfKzielYiEackMDpUkms8SCpeRuzhArHgJFPPptg5WEHdsQLBVIpI8CBTv9rOK8G1+KfzjOb8pHU3W15Zj92tE/n0FMUyF5oGTg6MoCS0aJzEsRgUNHxaguvrf86V/q303FHPce88Oq1mIuYMlWvGmFoSJp0LMZmJkRNx7JyGkxEYbgtRIQneO4UzI8gPuZEBDTmdYUNFioCcD8LkeEolvIcMWB6EQDAPUkABSAL7DQzNwRrVIOzAZgvKDMxKA+lo6BUOU0mBhSAWguEi7MhCgwtGbegxYNXreqWX+eHaeer+Y0dhU4/KjSra8IO98IU1cOvVagE41gv2KEzt0cknpcqsrwOkQA4D4w7oGhwAeiFfCXXzQToQ8r63xBVAPAbRCCSS0NJ0oUdTokSJc8UmyxR735VzSSn3ASvnWH+Ck1WAp67PAR87zbH+HPjzOdY/Bjx2ruc4C1ullDPADLDxXHd6R3OwXl8lIKXcKoT4VeAxIUQWSHCajtRCiC8BXwJoaGh4J4f5viKMzu342UeBqzCJzU75itdVh5RzKz0Isu4syaFjDG+fZGLaw7JEkqCWwFngpjKZwvNP/0pr09M8uvzTDLYtp+vFarSVLu752r8QbxhjJFfFgaFVBKrTVHmGcddnGHeVER4dp+74UZo3baOpaYj1lVt5ovYGbgg8gTeWwUOOgDvDT50Pc0ispG+4GWlpuPUUAVda/aYpgmUZlIUn+GTxxyzTM2zM+fAXXOwu3s6PJlbjMwQ5B/Yn4VevLfA7nV7YLWdje5DbFIZiRgmvYQPqIbncIV5mUC91wh5IFqEnB//aAYUgTGqQdiB2ltny7f1QH1a5WqYOQTfsG4Z5Zer5VAZ+8BTkLYE2ICAu1OtqRE2NVQK9qDqWESAFxhQMHoPqOHzunL/GFw/BIPz2b0A+D+FSUn6JEu8p3q0Q4XuQl4UQ3ahE9/ullFPnstM7KrBeXyUghFiCmla7ZVZsfR34BvCrc+z7TeCbAGvWrDmtk2qJN7IYN4txn3EbHTcRZxVOage+eT60KZuhcYOOLVMsq4ZgpoBd7SJqFXA92MHaR/6Gbbfcw6b8N7jp9x5kb/0i/sj+M1b6DnCirZm/S38NKQQVE/20ZPbSOnGAls4uYhMTpHuLLLolR9PDA+zbOJ+jVQso4sEQks9Fvs/fjtWimRaObmDn3Egtg2Y4SEcgNIfl3n2UFSYJBV2c0KFCmjw3OkSl2Y/frfIYe7Jwd0UM/9phktNxmFFiihapZofGTKjTICJgUjK9Az7fCEZMaZ6YGybz4E9CUxAqDbjUd/J6DZAHoPaU62rqqtrQNfs3qWirda+Syal1PhO8QsPtgnw3UOmACdig1WrIQZALwJcEby9cvQg+fwsMTsBMWuWXvZ10T8OLPfCJxeB+B/4CeDxqKVGixHsHHR9Rll3oYVyUSCnnCyHWoUKT//XVUKaU8ntn2u9dqSI8pUrgZmC5lHLr7FM/Ap54N8ZQ4iQSySMzL7JT66RChKi74hOsLv8RPX8yyLVLwVkfoOuSBkR6hon9eaKpGSYPZKh95EkqNhwgWRXg+uzzXOV7BUfTWME+/s73Nf706G+ypu9RAtOTiOcG8BQLBC6tJVeIMzNyHH1K4PIU0aQDQrWTMUWBGGM4tgEauENphLBxigaFtIdK3zC1iQHS7jB5UhiOj2EtRV54cFsd/LJQREJeE6waj/Picgs5LEE3ICWh3gNlQL+AYYkXyYIKSA3BtAYtjTBpQ8ilqv3uPsVGASCJzY8ZRyD4VSoJzP7Ku64VfnpQmX9as7YR605pYxMPQ1stHDgBcS+khyAVgHxRo8yEvAOFUXBXQTIJ7gZYtwRuuE3F0e/fAresgXXzeVvRhFqEOPu2JUqU+GBgkWWcAxd6GBctUsptwDYhxF+gJoa+A1wYgXWGKoGwEGK+lPLY7LrD79QYSsxNYnqcQye2UwxpjGDTXBYg1v4nLLz0PjzDj7JzeS2T3x2ka0eBbHcG2yUohgJoN9dyyTUv42jluN1FprUQAZlGSIEpCsxLH8Ad1tBfmWDo51nCdZLwimGmBqYQS0CTDu0vdZBoDFL0mlQwCjM6Dd/dyx2NIZwrrqQyZnAkH2B/SgAOplUkaCeZjJTzwNAavJkyrqndwVXRER4eqSehO+SlRrMPXhqBjVe5GP6+xtGkUGHBtAAfKu+pCihKFkV1NjYqd/Y9/XAgCj4dvBJu8MFL/Uo0LSlX18srNFrxIpEIcuQANz7W1gt8Ljgwqtzk19dDZfDkddZ1uOcGeHE/NDXC934MQ12wuAzu/jCcOA6P9EPDCpiegfgyaKuAHx2BiAfuvR6az1qn8uZpCMO9pR+qJUqUeB3yXepF+F5DCBEC7kTNYLWifLvOmsf1Ts5gna5K4IvAz4QQDjAF/Mo7OIYScyBSOWoPppFrY7iHiiwL3MXBf/8J1mCMyYSL9APj9GzJoRXAbRpMrGrEqvbjSaepqu5i5LhBR3MLL5uXcZncgk9Ls7u3lcBLh5l8uANn/wxOBppWAn6HiJNl58tRGq73EembounZo6TK3ehdKdz7NC713kTFv3wT7ZH78Vx/FXV33ERDg5e9k4KKCS/xWoOuTDXxsjEK0w7bRpbzZ037qKop0KFdRXA2Gf2vj0DcI1i51GB0v2R6TCIFqsDWgwrLFTR2zXPwNRW4cdpNwdFYFoDxPAxm4JE+2KpBKACiEiIRKDMEd0Uj5Mzd7J01By6jljZWsbhKZ3HV3Nc5lYXvvQg9o8pt3lMOcQ+saIbuDCxfAJfOh6cHYE8KpvKQt2FhGQyn4JUhaCuf+9i2Ay/0QEtE9SYsUaJEibeCjpcYSy/0MC5W9gIPAn8ipdxyrju9k1WEp6sSeACl/kpcIII1tVxWto7xnx+k8eprcScdcpOTSE8Ex92E7QwRqcpRe4mqYtOnOskchx0rlyKfO0L+U3Em+k0erryNA8Yi2pyjNB87Rvzf9jDd72DYsLQOGlfDBJLijMOJ/Tqbrr6OdZueY+rvO6mcB4U8zHSCv/w/aGxeR2Imh9HRR+hHj3Lzl75Ea12ARI2Xrfkwwwkdjx3E1DxUCBPNnqAlchMx02GTneeP8zY9MY3sqIuhlM7SKo1dSUGq31E91iXQrG7lJGyNusiYWSzDj5V3KGDTnxVkunT0hMC/Aho8cIUBT3XBT3J5rm22+PDiKC4DRukjTAWVNJ72Oj+0DQYnoblSPb71chgag4ypGk0Ho3BdGbR44R8moGsKskmYdkNFAI5MnP49TBfhuW5IVl94gWVLGM1DuQlG6QdwiRLvSSxyjHHw7Bt+MGmZdUaYEyHEP0gpf/P160tO7h9AhKbRevPNtN58MwCOZdFw3XU4cprwpW6Mv/o3am/WcLklel6S9uqkWyppPTzNE7RyvHYt4fw4G8xdxLQZ2jJ92Kt93Pp5E7Evh8uCQB0UW0FPOGRmJEUKWAkPkcI4vdMwsxU0A0I6ZMYmCS/SsWc0PLEaenr7eXimi6pgiFW6n4h7Ne1lxziecBHOSu6q3AP+j9JvlvNfUgfYPBUmI3VwNNxxgXkpbCxaHO6Pk+21kLqO43ODrSn7uYKgMCwZWmKxvDzHY6MCx+dg6UXsFsh0BRkdFFgjMOOCI89AbtLNtthqntnQw5985VlMESRHGmA2dPjahKapFBzqh/qyk+siIbUMT8GynBJXAGVeCJgw3w37j0FvF6xZBmVnqMILueF31qv93iy2LenstLAsSWOjgd//1lTRvx2HLWNwbQPcU3/27UuUKHFx4pRChHNyJnE1y2VzrSwJrBJohkHTDTdg08k4r+BpTuFMCqZ9QbIbWxhpm890zkex20VxMEwqbTJWXILP5VDfO8DMaIQVC/ew45Z1tIR7qS8O4ESK5KZhcq/DiX43Q2uX8eFdT9DineGEDyZnIOgH4YBmWKRyh+g2KpnSevCKGfrMSTpIsd2BNSLApb7b0Dtc1PugsuIW8jzF/dlNbMvcwlRBp3BQla3l6vK4fUU2/cCDZyyFB4t80YfTo4FfhzqVTE8SJnM6myagqDnoExJt0sFbSCMjBbScSd9IgL4pDbqAANgjGrv21LK/y0dVcw8tYgXHeAKbIm1chwvvL69pInMymfz1BDwwPH3yccQD62rguycgb4FThJEkfPIsbcHivjM/PxeOI/nRj9Ls319A0yAW0/m1XwsSCJzfH9ZEDh7epcKr1R5e25yiRIkS7xkMvJSx5EIP431FSWCV+CWCOKMcQHy0kRkZYzIYI00QITTKIinGKiqotwT7HDfD43F8yTaKvR5O7G5HC8Lf53+L2MpRPjnwI6479hzSFnTUR/BfP8MXPFvx7M6gD8FVa2HrQchkBbpX4q3X6O7NML3UgYEOBm9bRFrvoiBbSeJjp5QYzhAHRhYxavq4vL0DW77EpuJGkkWTzMtB9Gob4XMopkyc7Q6jE7CwxWbEiWLNaKpkscOGqAZlEuIWuSNu9Io89ogbshoYblLSj5lMo0dtwuvHmBmqhAZHiay0clZ/LjOPcKYZv+miwTWBxKFI5jUCK+RTp3TkG0VWKgctla9dd9t8iLvhJ9sgGoBPb1BO8a8yPAr3PQTJFNx+AyxffH7v8ciIzYEDBZqaDIQQdHcXOXSowLp15+erYOqwOg5lJnziHbSrcxwlWgNelc9WokSJt5ciWUY5dKGH8b6iJLBK/JIsBToJkg22MSaipAlTlC6yjoec8OAmh2HmWOQcYcSsQU/ZJPMhQmTYWVxJOuKhWBHhj33/hb+o+C94+/NMF2LcVv4gfxv7fcLRUUSrQ+yAYFXMoD9ZJDdZoLAixIH1d+KpcVEojyIbAniYRsiDWKlGRgKV5AzJtVcOs0FrQdmmGkjdRT5tAgItYCNTGgSgsNfEV1mE6SBNXuhybIrTmsrDKhZxN2vkPSBkAfuECcO6ssM1HLB1Ch5l354NO1DjqG6aAaAI0XqbyeO1DL0I/1Ad4V9vuJaI32YyEWfQgrbZqr9oABbWwbFBqDtFKBWKqjH1mrbXXntdg8ub1QIwPg6JBIRmneTvfxQyWQgH4WePQmsTBM7DH+v11gxSvjW7Bo8Lfu9qKNgQeoe8rwpF+N4v4MQQxILwhVsgHHhnzlWixAcXUQoRnj9z/hUtCawSv6SDV7DwkRBeCniwpaDJ7qEuO0BRmgxq1YyZMapdvXwm+F2qPcOMNFVSVjHFc+GNuCtzJHNRfEWbyHiSXJmLtrYjzHiD7GQZS0YOYYYs5DKBkS2wYngCp8zPN9s+RSa2hCEipLQAOg5Lcvvx6xnGdQ9FO46m+0n6J/DQgJDNGGxklSvHZp9F2gMgwO2AITANm6ULJljc2Em6N4q5tZWJGgdrSjKv3UVXg8NQh47hK1BMeOAFIA0ENHWM/KwTfI0Go4ADRsxh8bVpJl902PVYGT6fIBzTeNL0cfd1gn/eqUxFv7oO6kJw4AhU6pCIqCpCbXYSTQi4cwPUlZ3+fTh6FL7zHfB64Td/U1Uy5gpgmuByqQpC255737MJpspKnVWr3OzcmUfTBFVVOosXn0ci1yl4XGp5layUFIHQ22S01TMCHYPQVKXu7++Cy0vFTiVKvK0YeKhg0YUexkWNEMInpczM8dTfz7V9SWCVACBPhgQzWHjp1WK47CJr7J00T/Tw3dHPsE9fTIvRhd+foiw2RUZ6KHdNs7S8A29OMJ6rZItcRcHysCh7gGOeVtbN28Il8S1EjBmKlsFMNIh/NEs0M4XbW2R8XjUvRTew3b+OgMgwIyIIx8HSDPa5l3Fr8jES/ghuIQnO/rIqYOEWHlziOj7qyvGL0BhHlidI9vgQHkl5MEPzFQUi0TGiMkh00Sj3amVs7oxzbMJhvBXK/Q5Jr6A4LWBAQkIoEyzNUe1C5wkICtAkZCXY4K/PkDyiMXXQSyAOEcegOCx45BHBZ2+ECh9kLAias82eH1QzTr/7JZgpwN5jMK8ZFtSp8GHBggd2wLFhWNcCNyw9KYympqBQUGIplVIC6/Yb4Pv3w/Q0XHMZhENvfA8npuCffgh3Xg+L5839Pgsh+MhHfKxZY1IsQn29jsfz9vxqtZE8Xkjzh8NZhg672DgvyT82hykTcwz2TeCbNc+fSamG2AHvmbcvUaLEm8cixzBHLvQwLkqEEJcC/4qKZTQIIZYDvyal/DKAlPLf59rvnASWEGI+8E9ApZRyiRBiGXC7lPLP3o7Bl7jw2BQRuJiiAV1Os0zsoyHVz56JVWjdFv+86R66D9jEVkBmYx0vX3YDyXyclv2jVB0Z4bO+J9i1ZiWbytYzMN3A9YsfY2PVi6AJMnjpEQ3UJwaxRxLsjS3jZe/luGyLrPQQSKcQXrDRMIWNxEFKDSFAGC5qMYgN9zKdGsLUXNC2AoB2zcO9RpT7qxNotWlMTVBm+9CdMPZoN6lMEY8PjLRG47TE16LTcULipDWClQ4z48Cwprpih6X6NizT1W1KwjiQERBxSB9yUdjjwtMuwXYoDoGmC6wU2AX4yjo1Q/WqTcGHroepGaiuhN2Pw5ZfwNqvKnEFsK8XdnVDQxyePwzzq6F51vNq1SolsPx+qK1V69qa4Q9+U4k332mS210G1FRAYI7nHQmTRYi5QNMETU2uN270FtkhJ/jz/ATWUIqw5eHRHzdx1W/38Bvet/aruLYcPnYV7DwOq9thWcvbNOASJUr8Eoko9SI8PX8H3Ag8DCCl3CuEuPJsO53rDNa/AF8H/nn24PuEED8ASgLrfYIbPzomwipydeYl8h4XXqvI6HQZX376f/HskzblC+Fo+TwOTq9h5U+2szg1iSE1zMk8dS/38Ogv7uWLn/sbXvGs4dqqFykKjREqGaeMQs6Fx8lyZWwT6/ZvgjKbp7gdq1XDZxQgYhPTx5kmhuHYLMofYtxXiU8EuTyZI9u1lxrLxL3vx3BPNcRVlvhdvkEasp1sTdcyXViAX7q4rFZQW7eYLb2DDB+oxkxHaW01SA9DsOBQ3AfXXSl5WhhkklJNFY0I8AnIAQUJQ47qZRMEEmAFDaxFAtsnEAs02A+RbpgYgn/9Dnz8I1BVqYxCbQkbVp+8tiuWqyTtV8USnAwXarOC7NQiYNOEK+f46g7PQL4ITaYSU6/H44a7boRQ8I3P/XwMXpqCq6Jwa8Wb/XScGw4QMJJM5U1cvgIebx6buaubDyXgiVHwG3BnNVScuXUmK+eppUSJEu8MLjxUsuBCD+OiRUrZJ16b9nCaRI2TnKvA8kkpt73u4NabGFuJixwdg0aW4iR/hsdMMlIswzee5vbso4imPMs/C+MjMO6uYvVDj6MFPHRPFmhwCthxwUS5jqtP8EcP/x3f/L17kLpgiBqOyHb6Cg34tTSd9fN5xLmDzzn/xi2HnuISbTt7MivobG3Bn8nS6WkjZaiqRdMn0LQaFok6/E6BpEuwcNKrlEhBNV7OMsyoeJY2X4B6TzdhJ0pMq8etAVTR1l7Fd49DtwH798PqeZJoBIakZOWETu+IRqLokM4CIaEUQj+qrc5qDUwNJqRaEuqzX0gJqIJcs2AwAmvGYCYBjz0Fv/Jp+HYnjOXhPy8Cz+yPwYYGtZzKsnoVHjw2DJfNh6Yz5GQBbD4Mj2wDhEqe//TG1+ZaTUzBv/wIEim44XK4esNr958qQlHC5Dv4rV0rYnzFZfO9ZQP0dZusvH2aj3ve6NswU4QfDkDUpa7VDwfgt0uzUiVKXFCK5Bji6IUexsVK32yYUAohXMBvcw5t/s5VYI0LIVpRdVgIIe4Chs53pCUuTqppw6OvZ9LeSrz3ELHpaXTDxq6BVB+4Ixo3jW6hqyJK9c5Raus09Bv8JMwAT0SvJeP24QwY1BT6yRQ9DOkVdFnNhJ00o5laLOnCEBbfaPoDpqdjrB/cTv2JfkI5i4GyBSwUg/QF67AqmkH3ExZRPLjJhr1cXmwg1n8Yll0Claqjsk0WABchLC2FX8ty6kTIkW7o6IeWWujuhd1HBJcs0dFToJvgy0P9Ao0TkzaFAqoOxEIplxRgSpiwoWhgLM6hRR2cQRfWYRNPuSC6SEUQEylYNJtm1OAHnwHGrPhxHDh4GCanoKUJ6mebQXtMuPd11nS2DS+8ACMjcMUVUHdK4+idnVARVrn3O47CbWsgdkpqU0ePEnq1lfDC1jcKrI9WwsqQco1/pzDQ+LBRyXXhCgrLICpUztfrydqvznaBW4ORwjs3phIlSpwbkpLR6Bn4dVQiey0wADwFfOVsO52rwPoK8E1ggRBiAOUKdO/5jbPExYpAEPa24UlWwnQ3gztskhNQvxiqGsHqcHAlHNpcMzDpMHaDn3hQY7C5htX6DnLTJtI2cW+ySWwL4Ik7jLRX0R9oBU3g1vMgwTTy7CtfweUzL3E81sDUaIiFAymsoI+gYVJcW4cnVkUIP9VEqNWjmJetfYNXrpca3JSTYxiTOD7qXvO8JtSEl5TQWA+eRqiIwngrfLMIEzXQ5ILmFTpHDzkQB7yo5tAAgxISLtzXZzDaCjh5gWueBW5JcsLLdWUqD35lA9wyG9K7tfY1Q+CJp+H5TSp896QNv/oZaGme+/ofOABPPAHhMJw4Ab//+6phNEBrFTyyBQ4cB58JP3gKPncL9I4rPRgJK6uEw32wcg6PrIABy+YIHb4TBIQ4TdGyotwN8/xwLKX+qN/0DoUsS5Qoce648FBN+4UexkWJlHIc+NSb3e+cBJaU8gRwnRDCD2hSyuSbPVGJix8pc0i5GZfrOob2b6N7C9QthcQ41CyCGgHWBOSGC7zYC/NNA5eEy0a3k9qtkbRCuItZTKdIzu2lMjPAytxeXlqynj01Kxi2qpm04ridDIEFEzy+7GZ0O4+RKVAcTNKSCrJ2c4Gy+fPRYmePGem4qeMOLNIY+NFe93Fe0ATL58PBTqiMg38dzDjw3ZdhzALHA+k81Eahbp0g45FkbEFOA3ISRjWISoymIvaUDo7ALoBrfgFzm5d6F+gVktowZDLg9b5WVTgObNkGzY1KKI2Nw/bdpxdYxaISS243JJOvzcu6YSXsPQJWLSxuhP1H4S+nwTIgnYWpSfC64WgGPDnoHIXqIGRyEI+8Na+rtxtdwL110JdVUdjaUlVgiRIXnCJ5Bjh+oYdxUSKE+GtUznkWeAJYBnxNSvm9M+13RoElhPjd06wHQEr5jfMZbImLFQuQaN5aiu4Wqhcewx+HmWmwDR3hMbFklo7DMClhZmeO4nCW0T4IVzrI3DRFN4yMg8uVJjzQQU2kA93MMx0LEvbNMJYpY6KvnM3Ja/BVpmlY2EWb/zD95S6STQ6D1dPcEsoSO8cRaxiYzN20z+WCe25WRpWaDn/bBb84AaNToNWpBPNUJUzUge6W1C0oUDmlM3DUxeQEDCMhC7IIrxbXCMNBTusUBeR7JK4hhycseDkIv/M7GsPDgmPHoLISFixQEzlT01AWh1xu7gT0V1m2DLq7YXAQ7r4bjFO+nYYOq+fB6Dhs2Q2Hj4MehZsugUIWBsbh6tWwf0r1OuwahPu2KvG1ZjF85PpzvKDvEoYGzedhlFqiRIl3jlKI8LTcIKX8z0KIO4Fu4CPAi8D5CyxUDRVAO7CW2RJF4EPAtvMeaomLFD9Ca0Y6vVTfcDsTz/8jM6M5Ym0GnkAc9DLGeycZ6x0lWGtz8IUsOnD1dZDPgyzMijEHUknI5kDYsGzHXgaaajg6v42aYD97U6sY2ldHxgyRnfaQv9TD/OABRqRBuLqTZ42fcjsNmLy1mNbghLqtmXVS/0ojHD8K+rSaRXHGwPFBMQ41btA0Hb8mEBoEQgKjTGANQv5ZL57rskgNyGnkN3vx9MBj+6G6HO5YCY8+qsJ7U1PKRiFfhOpaaJ0H+w4oL6vLLoErLjn9eE0T7rrr9M8va4PvPAEH+0B3g9eA4wOABrEAVAagNQzXtIPMQC4PDVWw8yDcdDn43uMzRaNpmMpBVQDCZ6k6LFGixJvDhYca5l/oYVysvKqVbgV+IqWcmSu/9HQ7zYmU8o8BhBAvAqteDQ0KIf4H8OhbGW2Jiw8hBJr+SRwewgy8QPWGtVQXQ+gyAUYAl7cahy7c1X7SuW60cQtvEEyvCpHlU3BgN0yPKxsClwfaF8F1tQ7thw/R5a3ArPOy5qqtRBaMcvDAMjJ9YfJpN0lPBDKCSTOCx97Ffu05Vmu3v6XX8+w+1YLm7qvU46ABH10MPz0AmWGwdwA6OC5wV2ksqRZEHYhUwNYTEGtRs132AQ+ZEyYi6uDMaJDUyGyxOV6AzoBk6+MCzRI4XknBlviFxOcWTCcEV14paG6F8WFwrNeG/d4sw5NKMK1ogy27IJmDL38IRhNw33Pw45fg9vXw2augsw/GpmBgFIJR+JeXoCoM+Rk4MQDz6+AjV6pk+4uFogOPjMPBNMzzwYfLTlZibh+Eb+0D3ZGILHxioWBtq8ptK1GixFunQJ5+Oi/0MC5Wfi6EOIIKEf6GEKIcZepzRs41yb0SOLXWpzC7rsT7DCEC6ManwFwFru9BoPGXz7mA2ssbSQw/wFSvD4mO7p7CsVWOT3en6qGXy6nQWCYPB/ZCWwuktncREPMx7BhTrXHqKvqpuaaPl4evIie8FKQbl9cm7QTwim6OON9nvria4Bwu4AXyZMkQIoI4Qzb1XZe9cd2NDfD718G3tsHkAERnGwhrEio6BZ1CzZRU+qDKBdklkBwEOakhpzRoBp5xICsAiZPSyBtAGZB0wJKk0FROVpnk4R5I5QWFJFT4HFqeEXziw+eXEOX3qLwunxdWL4egDy5ZDP/zx3DlcpUwPpNRLvEzGcCEdAEO9kKwEbZ1QDEFG9tVu5mKKFy3+mxnfffYkYBtCah3w74UlLvg2hgMJOGPX5Qc35Gi95COXXDxWLnGF2/R+d1PgPsUkWjb8Mph6BqBpgrYsKjUHLpEiXPFOVN1ygcYKeXvz+ZhzUgpbSFEGrjjbPudq8D6D2CbEOKB2ccfBr5zXiMt8d7A0wzCBU4ONNXFVxZt3DMOZU112Mzgby/HqcmQcR/D4yqQyZ7c/dWJmkwGHnkIAmVg/MU2/N++hCnihOwkppFjffXLbHGuZEyW02acwFdMo0+lmTomuT/2l9yz+L/h+mVZn2IP20gwzWJWUv26ysHXvIQ5Zmd0AX+wCn5rKWTuhZAbBvvh//w7PPUgRGIga1UievdREPuVsBFxsOaBHIB89+yr02dfaUiJLWXlLsAGx5Skg4JXHrTAlkQ+Mk1yTY4/7PTgfr6MO67SSGdh+2HVuHjl/LkT0VNpePxZdXvTRrhhHby0D+Jh+PhGFYq0bDVGgMmkWrevE1rrYUcvDPTAswch4QfdBS1FJUpengBfFtZ5TtpKXEgStrJtcGng1SAx69m1qReSY3n6e2wKeS/SgcFhyY9+4XDnlRoLTv4G4Jnd8OweiATgQBcks3DzugvyckqUeE/hwk0dbWff8AOIEOIzp9w/9an/ONN+51pF+OdCiMeBK2ZXfV5KufvNDrLEewjNA/GPwvgPQXjBiFJ4cS/5F/cT81ew9jd+jw5jN9l4koEOi4WJHtyBLF6fSip3TvG4TaUhlYVgOoXpN7GkQUOxny5XMzVyhIA+RZRJcraLotQZeclh+tEB+lZ5GFz8HI3c+pqhGbgQaOjn0NZhdBSCQdU4+VT8Lshm4R9/Di+8CC/shlwWPD2wNglr18FQAaqikMhAqgfq3FCWgQN+QSqjehSiCwgDmVOt2AGPA4dSYFvocYGnJkHuJQ/5Vpt/eKxI0OVm9xGLIz0O/qCB/+Ma7Y28gWdegt0H1KzVDx+E3/01uPaUWScpVeuYPbMz+8ublbhoqYFHuqBvFFxe2DMJxQxUeuBZD1QIqK+Hn6ZsJBqXeS+8wloRhK0J6M2pJPi1s5OXpg5u3UHoGtIGw5RoEqaSJ53wX2VPp8q585gQ8KjHJYFVosTZKVCgl64LPYyLlbWn3PcA1wK7eDsElhCiAdWZ7YFT10kpe9/8OEu8Z/AvBSMKiZcg14W0BMLTCr5G2u/6MBm3F3fOh7X6Jo7f/z/xhY/gS0g8fsHooIM9K7KkBGxwXVfOaG013kSSrOHDlc/SbdSzRN9P0TLx6A4JLcbYiiuQnUcwltUwkHuUKs8luE+pK1zOGvLk8XH2MrSnn4b2dlg9RyisdwwO98KWE6C5IOiBfECFlBZUQX87LJ0HHQOAA1+5R/UO/M//Q7Bzq2RsQGD4oDBfUDisgXTUi3VrMJkBOw/4cFI6djKLlfZhb9HZMWLw1c15eo5nIZuiptnFR66K0974xq+jZanxmC5l4/B6hICPXQ5rZ9vINFaodVetVLYNRx6B431KC/ptZYw6XABpQO6gjf/qAQ6KAJedc93mO0elCb9dr4xHy1yqbyLAlQ3weKOLvd4sltfGSes4uuCKVdBS/dpjVESgdxSqYmo2r/YsDvklSpQ4iV2qIpwTKeVvnvpYCBEB7jvbfucaInyUk1EfLyoT5Sgwh6VhifcV7joo/6S6+4kc2qL96BUViEgcDxoe7xH0qI39uXuYSY1iPvw0TqFAc/0wgXCKg89BMQfmhypxf/NSau1jTLpiaCM2E7UtjBZr8BRz1HiGEbP9+USdxtBvX0+gkGZI9JGgm/JTBICOge8cP7p33ql8peZifg201UJZGJIWjE2qdjJdGWhuALEVykIQC6qKyJXtYBqwZqlgxUI1e5bJwGgzPOgRTL8oIQPoEvIWoAEGEoOJH5YhAhpOShAI6XT3ZrBtgakLpgYLnDiY5Yo1ATTttTNJ114O0zOQTMOdN7/xNUipZnFeLzR0HaJlMK8JBqbBKULeVJpPFCDsh3BCUNEV5prV557p7jiz79E7NOEVNtRyKmU++B+XGYS9QXYcLGCnJR9b4eLL12mvsbIAuP0S+N4zSmSVh+HOOfLwSpQo8UZM3DRQ6ll1jqRROuiMnGuIcOmpj4UQq4Avn9+4SrxXER4P5lo1UyopUMMAUxyniEFtwM3q3/9PpD/5NbpffJHcof+Nmd9DaHmQ/ktXYy+KoM8UsHIGxYiLxf0dPFT9YRwLWv3dGFgIISFbRH9ugOrycbKrmsgSY5o05ec55teHBk8l4IXPXAPdI/DQo8oJXdOgLwVPvgif/yg89IwSK3ffBrGI2u8Ln4XnXlRi46rLwQirWoCJW3U6XpD0H4fptCA7LQHV49BJGJDVQEKgErRQgcnRAqbmoAmNH91vsetAll/7gpsli06GPiNh+MI9bxy7ZcFDT8PuwyrX6hO3qjCi48DApEp07xiFqB/uuhQe2QrDElISqoGQA21ujQ+HwlTn4Ln9ypR02Xyor37j+QCGR+Bb358d06fA4znPN+VNkivA9zcJzLTJ5VUufvN6qIzMrfBiIfjND6t9PObFZbBaosTFTIECPXRf6GFclAghHuHkJJMOLAR+fLb9znUG6zVIKXcJIdafz74l3tvYFNHQcZjAjUUtV+MggUmSdHK46XJONN1OeXYj87/33yjc9x2WjDyHVT+PrtB8ZswI9Ue7QWpkHB+VYgQpQH12BRINchZm3zieCg8i4qMQdmNpOXRciHPIu3ozlIfg+jXw+MtgpqBMh0QeTvRDzwhMpNR2A2PQONsGp6oK7v74yWNs6wYzCbYBl3xUkNsKiTYfP/reNFIWoagrZaNJwjWCD18PX/p4kK9+ZYLxcQ3p81Hw+DjYC1//M4sf/j+dyBuLJ1/DkROwdS+01Ks+hJt3qf6DP3pJ+WRpGoynYTILegFaIrC2HMZt2LgYZAraKmBZA3z7ZzA8AW4DtuyBX/v43CKrb1D1VEymYHIaaqre+vU/FxJZVRXZVA7d44KJFFRG1HOOo3L8vB5lLAtKVHlL9g0lSrwpVCZHKUR4Gv72lPsW0COl7D/bTueag3Wqo7sGrAIG39TwSrynkUhG2MEEh3Dhp55XM4dtdFzkyPEA5YyTJSw1Jic6cVdlcX1yIzy1icITvcSjA7jqazBSJnFfhrgYw9J0JKDh4KCrSryOKVyTKWp+vofajzaz74owW8xNVGS6qB0ULCtbjavyVtDPd15LYdnwvVfg6Ai0L4TJFCSGlNv6x2+F+5+Fuko1pMdfgg3L3phUPZ2Bh/dBSxzayqB3Ej5yJzz3uIf1l4XYszNNvuCgaSZL1rj41Kd1Pv1RqCo3ee65Kg4fsfj1P3CoiiuxMDQGx7pg3fIzj71YVGPRNJWjlS/Ajk440KvsCYQAq6gq6mrigIShJPz1Z2HDvJPH6RuC4XForFGPh8dg37G5Bdai+XDZeggHoepd7B8YD0J7NRwZhMowNM7mVaXS8N0HldeX2wWfuh1aGt69cZUo8X7CxE3j2aNeH0iklC8IISo5mex+Tj2FznUG61RLbQuVk/Wzcx9eifc6eaaZ4CBeyskzzThdVHAjOZ4CJMMsYJIINfIQjyXqGcz4MYsx9IY4l9+RQ+vew0zeS9oxSdfFqdjXxbqpneyPL8aywdEFBhZyeAYxk2ZZJEt91GLzogYimR0YlptXxAJ2dV/K10Ye5kYOQ8V/AuP8/9MPz6gwWks5NF4OZVFo9cK910BbAzyxGRJp5Uwf9L9RXAHkiioPyvVqKx0BVfXwu78NN97go7vbi88vqakXPPCsYDoH37ofvnI3REKChQsM4nGL3n6bgB9aWl24TUillCP8XOcEWNAKDdVKIAUDsGEFvHBUVc69GhaTFpQbcEmtCnOmpqHmdXUBLkON33HUufIW+E4T+vP74SO3ndu1tSwl1rweiEfPbZ/ToWtw7+VKzAY9aswAz2yBwVF1HVJp+OHP4fd/7WSD7BIlSpw7BfJ00XOhh3FRIoT4OPA3wPMom8d/EEJ8XUr50zPtd64C65CU8ievO+HHgJ+cZvsS7zMEGhJwsHCw0XDhZg0uFgIFJB78PMlIscjeQh3JeC1PL7iK1lQHe1sXUll+La3FY6xIbsEzNsTIZJA7H/8Z9g0GI2XlFEybomai46XlcIK2wBC7v7aRlZ49uJ08Lsdife4V2muOEh4ehZ15WFoFjb9z3ok2mkqJwpHqn3JDFXxsA7TPWmt95nZ45Hn1D/72jXMfozwIzXHoGFPDqAhCfRR8JlyyHi5ZLwDBD34OAZ8Scd0D0DMIY0n41n847N6cZSKrU1mlcdP18MyT8JNJqK6CT98LoTnChV4P/NrdMJNUxzVNNZadp9gBG7Mhs0qfss3Q3Lwh9JhMqYT3nQehIg5VZbBuKW8J24bvPQTHu9U1+eRtsOQtduDQZtsBncrEFIRm1wX8MDmjLEK8JYFVosSbRr6aolFiLv4rsFZKOQow6+T+NPC2CKw/4I1iaq51Jd6nuAlTwyWMsgc/lVSwAgANPwXpJ4YFwsGRYAkbRxRINXjoKjYgRmF+/CCBdAIn66PWHsD2+Skm4Fd/9G3y+TBDNc0kyuqQD/VjxyoQlZJ6/xBmoYDbLDI1E8HJGlyS34JXWpBpgN0/A3sFtJ5G/ZyF6jCsaYQdPSpc6NUhbKo2M4dmjTo/cwf8zYPwqX9UuVdfugaunHdyZknX4KOr4eluCOlwWYMSV6+npgL2HlXbSwkTafi/j8D938wy0ZsFAQNTGk89pLFmVYyGekFfP7y4CW679Y3HAyUKYxE1W7T5FXVbG1Uu5poG6PClm+BEB0yl4bI1Soi9yvZ98NPHVbsZtwYLm6GpEV7eD0vaYEsvXNYCA3ko2rC+6ty07PCYEleNtZBIwfNb37rAmoul7fDTJ9QMYzKlKia971LifYkS7zfcmDQxhxlfCQDtVXE1ywScXY2eUWAJIW4GbgFqhRD/55SnQqhQYYkPEDHaidH+mnU9Bfj3GQCDFdEr6NSfxqen8YssbpFhnCg36z/nOvk0okoSjCQpJN34MkU8Y16KuQh61kvjAYMZysmP5IjefDO2OETKeRHhEeSG3ExWRJiMRPl54434pnPcdbyDJZqAE89A3VpwnzK9IeU5KQEh4M5VsK5Z9fEbmoD/8xDIGWXW+fQWeHIXHEuA9AE74KUdDn/1WcndV56cJvlhN/SmwNRglYTAHOe6fJWaKesbgpuugMHZ7YtZVZiiCRXSm5qy0HWV8O82YXQMnnwG+gehphrWroSy+GuPfeQo3P+Qun/3x+HqpaqKsCqijFJf2AOPboXdJ5Qf1j3XqW03bYOqcvB7oTIOz2yFsj7wmrDjOMg4tFfCT7vAcqA9CtFzEDD+2dDmTFItS9vPvs/5sGapEpmHO6E8CleWDEVLlDhvVISiNIN1Gp4QQjwJ/HD28SeAx86209lmsAaBHcDtwM5T1ieBr53HIEu8z9iaPSnji5lyPm8mMXw7eFILMKRXsc6zleuGXiDkTuPYGjnTRzbuJTY9g6/Gi1cauISD02BjNl/C4Aut5GemMD3NuI69grE4wXgows74Kp7OXk9H/0IKWTf/FC7yWfsZ/nhqN970+EmBld8F6QfAsxF815x1/EJAXQwKBagIw4k+kHlY0ATPbIcT4yBbUd4GBvT1WHzjpw4fu0zHmM3JH85ChVuyb7fkkR64aYOgpua1As8w4JrZuttjx7JsfmyGE70G1a0BEjMGji3xB2HVKh3LUrNXqRTs71AhxYXt0FQLr2yHL9wLnb3Q2QOXrlG5Wq/mJYVD0Fb/2tc4Oq0sKQJeONQL//shmE6rKsmWsBJYhaLyAPN7VI/CwQm49g54oAArm6FBQOQcK/MiIbj3Dnhuq5rFuuWqc9vvzSIErFqslhIlSrw18hTppO9CD+OiREr5dSHER4FXnfW+KaV84Ez7wFkElpRyL7BXCPF9KWVpxqrEG5hvwp7ZnuJtLohotdzl3MdT3ImfDNdYz+Oz8xwJt7I5sgHDVUAzJQ2tvaxO7cNj6xgzbUzHYuzyHGCitQV/T4jLt2Zp4i4mB77NSHs1u+zVHOxeiVUwaPF08Jn0d6lMjbI1V+TKye1osSY1iMIBkBko7DongfUqH14Pj+2EjasgOQYnBmanaH2cLPEoAnGdcZ/ONzvh441Q5obb6yR/8g9FhraCt02jZy987Ws6kTm8mnI5h+9/f5xw0KDRl2X5rQavlAfIJzJU1Wq0LgnwmY8IxsbgD/8MNm+FmZkih3Zb3HidRvsCF//6fY28pZLHf/AAfP034Cu/po5fN0drxiuWwYkhGJmCZBHCtrI5mIzB80fB3aVm0D53C3T0w+C46nm4uwhjFswLwIaz2Ea8nvYWtZQoUeK9Q2kG6/RIKX/GmyzuO1uI8MdSyo8Du4UQ8vXPSymXvbkhlni/scILVbPJ1FUGSHktvvw+glYeqTmE7QSDWjX3x+/A550hLypoppOkHWRXaCm1YggnPo3t2BxlPj2OwVhrDc80alx6aJw70x+j352hb7KRYsHFQt8hbg89xOKpw6Sifqb8BtMTO4g13wG6Cb4bQQTBvepNvY4F9WoBVVGXzkLgfuh/DHoBHNS3xdBZvhjGi/CTHrha2vzvP0vy9P0ebEuje49k1UrBCy/A0qXQMisytm2z2LzZpq1N5Up5vYLKmKChxkFc5qa+2k1Hr8r9mkoqh/jtuyGTTZJNJiCf5mf3SWpqvay7spLyOjehsBprRz/s6lDnuVZAS+1rX1tVDL7+CdjbBT/dDOHZ3tkNlbCtA1YsUDNXB4bhq3eo+163agq9Nw/rz2DWWqJEifcHbkxaqT/7hh9AhBAfAf4KqEBVEQpASinP+NPzbCHC3569Pcfi7BIfRKpO+RQJ4SGXvIPVmQd4paKFQVGFKydJuD1UiFESmLgoEjMmWZY7iJiWjEXLkY5kzBVimAocYTNpWjzf7mdiZglNrueROdWfZWloH2N2GVnHS7boo14fIykcYtrsIPRKCNz5pl+D4ygfLL9H5SAF/fCJa2FiBh49pnLNXDasXgg3roS8A4cPwaM/SPHyMy7cpsDWbRIJwbZtGm1tOps3w0c+AvPnSx56yCIeF7z8smTDhjA7d84Qixnc8aEg2w/Aw0/DviOwdhn8v/shn4PRXIG8IyGfAQqAw+BAkad+7nDlR+s53KvT2AB/8R/QVAPREPz9/XD37VBdrd4X9+wPUk1TzuaOc/I1T6VU6LKtViXf946r0GFZWD1f51LLxUw2q5ZotOTaXqLEWyFHgeMMXOhhXKz8NfAhKeXhN7PT2UKEQ7N3vyyl/L1TnxNC/BXwe2/cq8QHnbC9hbZ+E8dzlAcCd3CJsQNdCBw0JIKEDHJz7hdE+xKMl8WonR6i02yhoJkEtBQpPUgRgxmvzmbpxVVsYmnkAH2JJorSJGv42Vq+lg3T29B1i87mVeiii1qaEadOcVtZyA6D7gZv9Wn/AzsO3LcFDvarCsBfuRqqo9BSA79/L3x6XBlZNlXDTwbhSELtd1UtHC/YaMKFyw2aLpAJ1UKmvV1gWbBjByxapIRMOi0RAtavD/ChDwV/2XfwpquUoAv4oa0RfjIFPXsgH9dgRxYVm9RmlyKZdJZKfxozFOLpvcoo3nUcqpsgqcPjP4bKeRB0Q8VuaDbhc59QiexZN+zsheqAqixsqYR0DqaykClAdK4M/YuUwUH49n9AJgurlsNH7zw/kdU5CVEvxEozdSU+0IhSiPD0jLxZcQXnbtNwPW8UUzfPsa5ECbyBebQHHqdyYIDJhUUONc5Dkw6TMkpApHDbRdx2AVGQ+HJZTKuIT2QxpE1BuEBKsvgwydMv6xA5B4/HpsnfxYl8M1fGXsTjK9JVM4/DVgNXl8Xp5AA2OaTsJ8UQYctNZUcXZiYDOFB+CdTfNud/4NGEEleNZTA8Dds64Y416rmyiFpe5Z4GGM4pS4eYGyq/7uG/JdLs3xekmNXw+x3a29WsyswMrF8PwaDgs5812b3bpr1dUFV18o+YlMo3amk7vLIbegchWAmBconRIbHQ1Ph/2SJIB0wOH7KwKiRSFzgmJF2QGpntixiGzkNgJCAzDg1N0LcZLlsLsgmsMdhQC61Vasbqzx+BZB7aaqBzAuKzk94Tk0p8lpe9vZ+Pt4ut29X4Guth917YeBXE42ff71SkhAePwtIKuKH1nRlniRLvBdy4aGOOJM4PMLOhQYAdQogfAQ8C+Vefl1Lef6b9z5aD9Ruops4tQoh9pzwVBF4+nwGX+ADgv4KmeW3cf9BD1fD3MBv7GbNipIs+gmYCU+ZJ530EzTS+TBbdsahxhqjwjzKoV5PHgxCSjO3FcXQmPGFCLjdXN+7g+Eg9B6dWUumaIepxsTxSybbuSgZTkkOeIoVQDVWBShZbB7gp1M8ybTlCShjdDPGV4H/jHxC/WzmxjyUgnYey4ByvaRZdg1rfyceXXerlr/8KHnggw/S0zo03emhudrF1qwrLZbOSb36zSDJpsWKFwaJFJ79yo2PwH/fB9AxccyV89TMwnYDJjMMfb84zXJQMRdww7QGyqELqOLrmofOQgTtZJNhsktUdsg4U8yA0mMkBBXDHJcU2jRmvwNYhNwMhDVa2wWWtEDTh8BAsbILmMuVK/+RBZVuxcw/c/4g644duhEsuQguEsjJIp9V19HhUNeWbRQj44irwnFdX1hIl3j/kKXKMobNv+MHiQ6fczwA3nPJYAucvsIAfAI8Dfwn8/inrk1LKyTcxyBIfJITA66vhnjXwUradkXSAfO44mXwHE9EQWbMOywgzUuVFSItQMomV9rBk9BBHquYzqcUp2CaJXACRdTB8BSqMAfxeL/c2+dlbzDJNDce1Oh4/7KYyq7NVD6N585SZg4wbCfqMCkblOv4ik8btuEDoYOfnHG7Qq8KCrxxX3lHr287tZUop6eiwCAYN/vRPo+j6ydmxgwehsxP27bN46ikLKfK43Vn+f7/r5rd+y48QgqeeUzNdtdXw9AuwbDFUlsMT3ymyuFqy8CMauzpcbH05TnpsknzKQAgvDQ06lVUGWcdmOJNl2nawQgZO0AVuIAVIyA8I2ClxcpJ9N2pkyiFog1uHvzoCyyOwxFTbOg5kiyqsCLB1J0QjymfqlR0Xp8C6ZNb2YnQMNqwF73mG+EKlxtAlSiAROJQSGU9FSvn5c9lOCPEHUsq/fP36s+VgzQAzwN2zB6kAPEBACBGQUva++SGX+KAghY3Hl2ARTYhgM4nCEUJGHkMzyHkb8KfGkVqUKU+ByReqcPWl6L+6ieP18wjoCciBM+ggwy7S5S4683mKgSlyejUIi6qMQ0dC40AgTMHQMRyTaDLNpYFXcGkFRnzV9FsOrbkhcAXBN0cH41kaytTyZnj++RxPPJFFCLj0Ug+3366mUCxLCazmZti50yKbB+EyyeeL/PsPitxyi0Vbm4FhCCxbhQgFJ3vojY87hEICrxduLRO0hE0aG2t5/HFJsejgcoHpFUxiM5VwqJ53ghNPL4SreNUtUPkM78pDQocv6BBy6OiF8gqNQwX4cAh2TkG8Ei6fB1s6VR/Dj82GRtvb4Knn1P2rLlOhtFRaOaUbF8lsj2HAFZedfbsSJUqcHQ8u5lNzoYfxXuVjqImo13BOfyqFEB8CvgHUAKNAI3AYKFn8lTgtGjplNDNKJwIImQuoIMIoTyLNJgZzq5iZGSPv8jAgvsgQ2xiZqCOd85NMBPGMpInINBMVcaKRSbK4OFyw8QVGmG9VsWjw23TnbiXpXYju9lHj7mOVfydZx42l6bQaXUwHW8FTBdXXgHEeMaQzcPRokfJyHdMUHDxY+KXA0nXVP3BmBsJhgZSAo4TR4JDN//pGgjWrXdx0c4CpKY2xCbjjFggFVcuXhQt1Nm2yqK6G7l7J8IRGWQ0k0xbJtEMwbqCX6XRtl+TGdU5sb4OUAyuAcpTI2m/BiICoBgGhLIMrITcNJ9KwMwUFHX6QgL9ZAzcuVuHPV1PUNl4B9bVKWDU3wg8ehkMdysj0Vz4KZbG39VKWKFHiApOjyBGGL/Qw3qvMOfV3rr9F/wzYADwtpVwphNgI3Pt2jazE+5cmVhGlFgebMJXouAg67TzV8wDj6WlCvgpSE1ehVS/kcH4+g3ssHKERi44SCibwBLJMT0Q59PRSmld04jFgMBcmNJpgjVbkyop+JnMNjJkmQS2JbhZpcPpozXUhhMZI9UbQr31HXtvatW7uvz+NlHD99SfjU0LApz4F3/8+VFa6WLw4x/BEkfExm4Lm8LOfFdi+LYemwW98QWWUzyTgH/8dxiahuszF+g2wd6/N8T6NsgqTb/x9AZfLIJsB13gRe8og59FhzFFlhAjolNAkIAHkHMhrqsuzDUQFWIJkFxgmPCNVM+i2JvjWbvjqOjBO+ROhaTB/NlTa2QMHjkFTHQyNwsu74I7rzn59LAt+NNut9BMfu3hmvkqUKPFGVIiw1Cn9PHmDTyicu8AqSiknhBCaEEKTUj4nhPjfb9/YSrxfEWhEeG1o7hd7fWw5dhetdWNMTXmZycc55EieqgGrRYcsZPUATAhEwcFl2Ix2VZAaDRKsS+JE3URavYxMG2y093B3HP5v8A5eMh0a3L2szB8gpYWpctK48s+A750RWKtXu6mrMxibkTTUvfarVFsLX/86FIs6o6NufuOrFlsTeWamctiaxtGjDv/4jyk+9zll17B5J4xPQUMNdPcLViw1+cI6OP7n8PRzDsmUxDRtpKHjGA5GTIcYsMdC2TcIOCGhWsACVNa2Y0ODBl6h1NMEaEjyKUmis4AmJV7NxeGEwWA7tJymAs/lmm2onFYtdTznmLOUzcKhQ2oWLHsbBM9QPFCiRIkLiweDdqou9DDeq7ylGaxpIUQAeBH4vhBiFEi/XSMr8cFhdAZePgoNcTdWro6EhBds2FmVJ+2R6MKBgiA35sYuE7inczgFHSNsU0i7SZs2uaSXw7ti7FjwZTYb49xV08bfeoKMsY5jxSOUi8MIzYsj26l1pOqiLE7/UU+klHAoi7651yIlvNKls+04aNvgE1fAklOa0QsBpgl1dQYrl3nY8lIalwGGoQGSRMIhlZKEQrPfzdf9BgoFYMdOh8GBAtIBJ6eh6VnKKn1UtRnsGwa7LK/CfziQFrBVg37UTFaXDZYOfaigflHidNlkvpsgU5CAyQM/sqm906SxwuQLV0DtHIniBQvGUrDtKLQ3wvrlanbqlV3QPwS1VbBhlRJipxIMwq998eT9EiVKXLzksDjMyIUexnuVn8y18lwF1h1ADtXg+VNAGPiTt2dcJT5I7OpWjYm1WSuoAw6MeC2mAhK9KLFtgfA42CGN3KSHCcpxpQpYPQbFKRfFGRditWQqJxhMVGD6Yvwia3OFx6EcF+X6h5CiGxwNIfNgLDmjuHIc+KefKLPN370XIm9CCEynYdsxqC+HbB6e2PVagXUqX/iCyX33uejtLeA4Fm43rFrlwe1W4urS1XDshPLBaqiBlYthZBRSSQdDs3F7BbmCwETHSBpEZ2BpFexZ4oZUFhIGOBZMCZXY3iFU6HB3AYIGWBpkBdyXVIoJN6DBIo3RMLwwCeN7YV4GFpXBFQvBdKkE/B8+CcvaYcNy6BqEY73Q3QW7DyoRuPcQ9A3B3Xe80WasoeHcr2eJEiUuLKUQ4dwIIcqBLwJNnKKbpJS/Mnv7F3Ptd04CS0p56mzVd857lCU+0OQKygqhPGhjkyQnYVSGGPcVVZ6QVJEs2xZobgdHM7BdGtakH6vfgJCEPoFRV6QYcRid0mgJCVJZmI7aBNFAq0B4fh2sfSBC4Fp7xjFpGjRUq5Y4HvPNvR7TUAnt6Zxaqs+Q+N3YKHjooSh/+qc6ExM2NTU6X/1qkGRSAJLBAcmHNqoqP79PzY49+wxgSSxHQxYEGhY+l4MnDDIP//k6+JO/0+gqd5MvFpXPAjmwTbUAZHR4wgGXBiEL0hnlVSo18GoQN5CDDotCkqN7BN0aDAyo9+qyNpvOTpv+Hli2xIUQAtOA8UnYexgaa9X1i0Xg4DGVoB+aFajDw+q5ioo3d03fKaSEqSll5XC+dg4lSryf8eBiIRfJF/bi4yFgE/A06r/VOXE2o9EkcydvnVOjwxIlTmU8CUXHImu8RB8HOZKvZ/fYJUwZfoQpkS4NoUk0S1XeaS6J186geSTTlCEcW30YZ8WY5SgvKikkgVNbPOi1ajlH7r7p/F6P3wOfugoe2wm1cfjwhjNvv3ChwTe/GWFyUuLxCH72M42f/QySKRu/zwEkl16qxJhlGXQc1/jipwy++6MCI4MWXpdNa5OHy6/UqSyHZQugvkJQzBtMFwQTIwYUMyAK4JGor7emBNUxG01P4TT7VIPCnAtmbDhmIUIaQ3scdj4KXrcgUS44vsXij3ePMDyYRzd1juwNcel1UdxuwYJmePkVJVrg5O2rs1cDA/BP/6IE1pe/BFXvYlqHZcFjr8DBbljYCLddokTw/ffDzp3KkPRXfgXqSobVJUq8hiwWBxi/0MO4WPG9vl3guXA2H6xS5kSJt428BTlrkKPFfehDNhX7hxmvjyJ0iSuaw7J1pBRgSGRe4BY5Vvu2EV2Z4EhgIR2H5mNV6MigRM9pVMaLzLht1utuBkd0XpmG6iAsqlCzS+8G7XVqOVcCAY1AAMbHoa8PamokP7xPcs/dgpdfzvPiizmiMSiLG0SjIZqbdX73yz4OH3a46y4YGNBwuQTXXANDY1BVI2hrFew8KnB2OEyNB1VGejavRJYplS9WZx4naIDbrRLOfDoYBZgpUsyZ/OzPk6ALyEpGAj683klykyk0TUM3LPJmitvDfj59u5uKGFy2Bl54RfliZXNw+VoIzvYxtGwVen21DdC7yb5OeHk/1FfAloNQVw5NZUpcNTaq675pE9x997s7rhIl3gvIUi/C0/FzIcQtUsrH3sxOpcLpEu8augYj3dtx+zSat3fzf0NfgWkNqUGx24NeWUQaAntGx23lqbN6qCyOIXWN+vpejKDFgb6liKIgHrNxVxYITpgEc36+OwY+F2QtaI3B51aBcYHTCfJ5m0zGIRw2ftnY+VViMVixEvbsEfz/2XvvMLnKM0/7fk+qnDrnpJwFQoAIEjkHY7DB2DiMbRzHnvGOZ9Yz653dnbAT1vNN9Iw9zjbYZoxtcjJJAhRRzqlzTpXjOef9/jgtJFAr0kICzn1ddXV39Qnvqe6q+tUTfs8ttwg6Oy22bs2BKhmJK+zeU+Laqwt0dPiRUnDttSrLl8PBg/Bf/wVbtzrF+fu3O5GiTEYQDCgoUhJPKFimih61KFkCPCb4JYwnYdwEDIjFEB4N6ZFQLIKqg+0F3aRklyjl/Qgth18V5DWDQk7nmfUWd99oAwo3XAFN9TAw5LjPz5t5+Nqam+D+TzsRrfqTDCTmTRjIQLUffPqJtz8WuaJjB2HozvijXMFJCXo8MDoKqdSpzyt0cXk/4EVjLpVnexnnKl8F/lQIUQBKnGQWzxVYLu8Yfs0mMVRiTtU4BcVACiAF+EAOqphZFQzAlDT6BrlePEuwlKGkaIwXy/CrOcIiSVUmxN3TvWS3+rhqrsIrvdAaO5yiOjgGB8Zg1ll8rejqyvHjH/dSKFg0Nfn4+Mfr8XoPKz5FgQ9/CO66E4RQ6etT2LFDsOegoDym0NtjMWcB3HaTIxgaGhzbg5/9zOnIs2147jm48GJIZ2HbFhsCNqqAcFBlYFTgCwnyqiRraE6YKeiH9rgTuVIKyJjX6bBMAKoBCRtyGcjZgIVUvWRiGlCCIZMNv8nyn5U2X/8jP4ah0NkJ+w5CtgVmtjoi5hAtxyj2nwzThv/cBv0TAuuLixxxdDosaIM1O6BrEGIh5+dAAD75SVi50qkJu+KK0zu2i8t7mRwW2xg928s4JzndbJ4rsFzeMSqjCjXJJMPDYaIiwRzPTnoLzTCsOJ8JMoAtqR/r4uPlv0L3xCnZKhomdcEhVL+H8+v6uOz8Yei8ko8sVVA9sO4leGTY6Wi7ej6gQDx3dq/1178exOMRVFf7aG/PsXFjgksuOboK3ummFNTVwSc+4ecbf5amp8eiqlrjjts8NDUe3jaTgVIJgkHnq6JAKgHt7ZLdu0xsW6IoUFcHiqqheQUeA3weyWjCBq8O0Qj4gyA1SChQq0O5D4YlDKTBVnF8tXSw4jCaAmwQXlIFH5s3QVeXl84+hVVrobYKVq93opM3X3fU5Z0U6SL0p6ExBN1pSBWh7HTnCgbg9++EeBqiQSeSBU568L77Tu+YLi7vF2w3RXhMhBAxYAbOuEAApJQrj7ePK7Bc3jGEgA9fO4dv/fh1miptLq95lUQkwuuZi7DHNUTcpKmwmzt4lXB6kGyrBy2iYlg6c9KDxNX5zJgWZ1FbnmsXSAIeyR89m2NzwYacn4G4wmASrl4M9ZGze63Foo1hOC9WqiowzWNva9uSRx/NsnlzgRuu0/AHVf7wD0LU1b45jBOLQWUl9PQ4nlN1ddDfD/G4xO83KZhQKghSOYtAWKMyDCIAIzkVJezHLthQGXa8sWxASPAoaF6JWbSd+7A47JmXm/AQqwWpYJqwdatKICDo7IHKcif9VlUJBzuPvB7YP+gcZXrN0dYNbyXigWV1sLofllZDzHv87U+EoUPVKXqaubi83/GhMZ9THMj6PkEI8RmcNGEDsBlnss1q4Krj7ecKLJd3lMtuv5hHHjnI0M5u6vaOcc/0n/Hhql8yoNWgCCj3JBGaj7TiY7Qxisc28aDgK5Uz0zuHjy8dpzkcJojGJlKsDY0TWSiw4nmy6yrIFsGvgF2El7ZBJAALmw8PUj4Z+siynwRNBGnh9Po8brihgl/+sh+AcFhj4cJjH2f/fpM1awq0tGgIAe3tJoMD5lECS9PgU59yirQzGfjYx6CrC77974L+AYFZsgkGLTx+D2XVMHs+WEXYvE+w9CKV117NMooHigI0G2YLGAO/aiLqbRK9CtiH1JBjhgpeJ9pFfuJaAkipMHOaMwzatmF0HK667PA6X94FT29xvr9tCVw66/iPlRBw6zS4uQ2UE4gxFxeXM0MWk62Mne1lnKt8FVgKrJFSXimEmA1M6n11JK7AcnlH8fl1/uDPb+Rf/72R8e0vI8ezlBRQRJLpy5uIixlkR9vJVxtYXhUrLygWyxgVS7j1Yo3p4Xo8E2Z4Q5SoMFT6hlVCZQXIQW05yBR89G+duX5+HyydCX//GSd9dCJymDxLDyqC/SS4kzYinKJBFrBwYZiaGg+plEltrRe//9gKL5u1UVXeKIQ3DEEyaU+6rcdjoWljCGESCJRRWekhGJDMmgmd3QptMwxCMQ3TdsbibHq9QC5jsT+jcfvtEVatF7T3gJlXoFui2Ca6TGEpGuE5Ktk9AtMGqiShigrSXWnkuIUQ4Pd78HgkDz6Y5atf9SOEYOWqIma6RFVMwzEvhZ5xCPvAltB7Cq/XrrhycTmbCDdFeGzyUsq8EAIhhEdKuVsIcYKPjq7AcjkLTJ9TxWf/bAV/9eM6eg/sp9oepW5hCzTMB73AWB3ohTFMYZEp1mFb9Uy/3stA636exsONTMNAZRFBrpiXZyhfYnR1jJpymD9T8sprgo6DTo2SocI6E77/FPzhXSe3PolERaH0Nq+zqspDVdWJB/fV12uoqmB01EJRwDQlra2Tt9K9/PIYL744imLobNpVoizWwNp1KfI5C0MTDPV5mDNTIxaFF14qYOfztNVrDA7mqPH6+MydHh55QjI0DIm8jbeqQMAnGM1I7KjJJ79Y4OmDQUrCoMwfQJ8bo7C/QHbEZFqLQVurTXfcYsM+m9GhPH//dyMUSoLvftfkP/6tnHvvjXDFHPjJMGgKXDYb9o3Cw3uceNjtMx2neBcXl3MLHyoLOY5b8vubHiFEFPgt8JwQYhzoPO4euALL5SwxWJ1i1ucjdK2fi9ZTRdITxMyBUrAR9vkMF8cR0ub8Vi/nzy6jozxJJQGGyZCkQAV+ajD4sreGTyyVrG8SPKXmiNuSzj4Vrd8goAqyBcjE4aVNcN/VJ5436EPjKurYS4IWQqcVvTpVKitVPvOZEM8/n8M04QMf8NPUNPlTc3DUZm8iTFr6yecsgkFJFzoNFQqFcQtbWvi9krpagc9j0mv52DGqIBoN+sMWmgLXXC3IWdDeA1oyS6hKZ+eONMWxHJru48abvFQFDDY9JxkaksQ9KtnmEpvicdY94lTX9yiCDetL5PQgmk+QLVn8379LcO+9ERrL4Ru3O+stWPDd1RD2OBGqX+yEr18EoZMcGP1+wrYljzyyh82b+7nxxhlcfLHrhuryzpHDYjPxs72McxIp5R0T3/4vIcSLOOMCnz7Rfq7AcjkrhFAJhm0uutrPXQU/B3uddFK2oDBbn0lFxGRBg0rMGqGw6ddogQIHF19GWAsS5vC7s45CmQF7q/LUAw0ZhcebLIpDJmKvTiEDo0XY1Ql/8E9w1Xnw0RvBcxzd1EyI5tOsvTpdmpo0PvWpN5+zUIJnNsLOboj44coFcDBfTlamMOwCyy6JEIkItmyA9qKB6oNZTYKt/YIDo7D0Uo2dv1NIVEqKq/L88IUSetRm+nk+gnMVIjGV1oiHSCZHnddLIqDQs9cm3hdnR3WI114uQLd0ug+DCgQisNTEvzvLtqeypOuD2JqJpWrYKmSPqOQ/NGsyX4CSDQHdqbUazjpeZa7AOpp4PM/69b1UVwd46ql9rsByeUeRCHcW4VsQQoSllEkhxJGhvW0TX4Nw/KI1V2C5nBWWEKQeD2FUgh6Fsja4oO3ILSb+Nde/jGe0hwsG88yoF4RqnfTgkdhSMiJtGoSCEhQsbRRs6LDJbwShQH4a9E2DJyVsfNqxOPjcSaYLzyaPr4MNB6A+BokM/PUvoCqo8cFbYkgpEUKQTsOi872s3w4eKdm3XrDFEijSZuN0SbqUofhYBuQYYFEagl0vlHHTtHpuXq7SPR4hdjDAtm0ptm/P4gspjK0wGH9UA92AacKxz/BLUE3YmieraQykfPiGVVRdQVommq4yfVGUQsHxw0oVYV8CfCrMKoOdI47AmlnmuEK4HE047KGxMUx3d5KlS09+1JOLy1TgR2UR0bO9jHONB4FbgNdxqhyOrBSVQNtkOx3CFVguZwUFQd3JpN8qmqFzI7onREWwESb5hKUIwXxVZatlEUZw3mLJ0qTKEzvB9MOBuRZRVSItjfE6ePhFuOcGiASn/rpOlbFxWLPR6ca76HzH+gCcnze3Q3OFEw2KqtAxAI3znN+LCe+DAx0ghEJFGPasARm1IVDCGszQtTEHJiBHcewXnHmHlIbZ/KKPS26txO8RZNM6mlYkEFAo1voYf7UcUJxGQgWowOk8TOpg+aCvl4KaxB4OoSoa0UoPl12hMHOWQToLaPDdnTCSc854QyNcWOe8Gk2POZ5ZLkejaQqf/ewSkskC0ejb9KpwcTlFslhsInG2l3FOIaW8ZeJr6+ns7wosl3Ob1qVQ3gy6F3zHnkpwu2ZQicmQtLnBULHbNKyLoCNv0x4qkfVJjHEFw1Yo2pBIv1lglUqOOaXP4xievxPkcvC9ByGTdaI7W3fBVz4NwYAjqjy6M7/RZzjz/UzLydYdid/n3K8VQGKBXoScdBSaOfEVcD54CVA1CIdJWSpDB22+9mGFLSbs2O4nnUmRGgpM2DjgKCIfTiDcAsLAAQ8oAbBsSukMCIO4aVIqVVAWFYSDMJyHeAFaw5Auwc5xJ73pcmI0TaHsdF1WXVzeBhLXaPStCCHOP97vpZQbj/d7V2C5nH0KQ5DeBf5W8DUd/ftw1QkPYQjBFfph9XHQD0iYXa7wykGFfEigpQT+fmiqgpDf0R6KAqNx+PFjzqg+Cdx0GVyyaMqu7pgMj0IqDY0T2aCuXme23/SJz0q3XQg/X+XMYC6WHI/QyFusJtpanK9eCds3ZSBRAkuC0EAq4PeAUQXFNGQTEImBprJwtsTIQX+fMxexqirMkmU6mxVIJwT02M7IHE0BjwLlOBrtoA22BehAAKTANNP0dtl88oMqug4xAQENulJO/dXVbimRi8s5jx+V8zjLDs3nHt+a+OoFLgC24LwSLgQ2AMuOt7MrsFzOLnYRur8HVtYpmGr9GujRt33Y5lqnYzCbg082Gqw7AHYJampg3gy4/VvQOw6X1ML5jZDJQ2MNlEx4fCW01EHdGZ5lGAo6gi6bczrspITwRJ27lJKDW0rs/G2ORMrm2hsNPnalj20dCg1HrEtVYcY0qK+BVb+D8RyOIpMKhHwYAR2roGF5VTCLaH6d8+erLL88gD+ksHsv7N0Is2fDcJmP2LBFz0sJyKScSJbthSofLPI5cyPbLBjWcUJbNhDHLpY4sLmD55+r4J57Ivg0uH8ebB2FsAGLJhmunC3Byx1Od+GyRtcDy8XlbJPF5nVSZ3sZ5xRSyisBhBC/Bs6XUm6b+Hk+8L9OtL8rsFzOLtICOwdaGMy4I7imAFWFj98EP3sKhsZhSYMjYGqr4J+3QEcA1Fr4rwJsehy+dKezn645Ua146swLrFgU7r0DHnnGiabddQtUTXhEvfhiib/7uySxmCDkFTz5cA5ZtPDUhxiOCyqjzna2dEThQAL+29cMfvagpD9jEAzoXLbYGWVTGdPpHQpwzy0RDvZDe79CKKqRSEHTXNgLGAZgQP9LYzCSnnBvl0AKBgLwqwLhFhW7wUaWh7DzFjk77aQjCZKIW3z2syMsWuRhzhwvQRWsUejMQq0KtW+x11nVBS9NuMhUB2G6a7/j4nLWcVOEx2TWIXEFIKXcLoSYc6KdXIHlcnZRfVB7N4y/CmWXgefE6cCTpTwKv383dA/CcBL2pWAgA50+8BbAUCDthQEBA6NQX+mk4mwJZccu9zot0lnY2QGVQehol3T32sydI1iyWGHuzKO3f/bZPB6PU5OjqhCJqHQeKPG5m0xe79TpHHDqtl5PO1m8uxoK7FyT5KZlkmDM5sZbPHik5Nk1glRe4bKLoK0N5s+DA10wPA7zp8O86dBxEH67CjJIEnELpBdn+rbEqXJPQzLKeTPBjmi03anSPVritecF+VwMJ5KVJ50WPP98gTlzvDyzGV7d5WQod3bD125z6tsOEZnobzAU8E/uqXpc9uxxUpuVZ1gEu7i8X/Cjcj5T/ML33mGrEOJ7wM8mfv4osPVEO7kCy+XsE5rv3I6DzOWQgwOI2jqEZ3ITpaEs/HI/tIXh5hbnPkWBmkp4tBMGMyBspw8xN9FUJw1oa3UEVfcgIOEDK6Bmit3GX9kGP3scdq2y2LI+iWWaVFcr/OX/DvKZTx19PZZlMzoKQ0OOn3wkotLWBh4h+dytMDAGY0kItUN1FFqSJvt0aG7W2bWryJO/zmHbAl2HT97nJRRR+H8/haAP/uQTEk0DTRNICUk/zFkCkYBg5w4/A8OjYKs44qoElNB1hWAFlFmSD98u+Mt/N5FWCkQWdNVRpdg8/GiWm28L0T2iUBFxRuZ0DkM67wisbFbi9cJFDYKqoCOuak6jm/Opp2D+fLjmmrfxRzlJ8nmbdNqivFx7o3vTxeW9RgabDWTO9jLOVT4FfAFnJiHASuDfT7STK7BcznmklFg//SGyuxMxaw7axz456XZ74nAgCf0Zp7DaO/Hf3T4OfSlonXBxv2MG/Ho/lBRo0OAnn4cZ9ZDMgNcA3xnokJ/RAGoWdm5NYRUKoCoMDZb48Y8z3H2XTij05tD8ddcZPPVUHik1TFMSjdpEIiq1EwOga8qc29wWZ/vRUQ9r1+bo7TWprPSgKIKqKoWeHpuOgybLVxhcMAdWv5Ri2bIUhYLCl77k5dOfjTKcgGkThehXXWnwy00SK39oPRbgZf4FsDCYZ9WaAv8xqpMbHKK2TaFj2AsjBfCHEYbCjv0lvvVdk2uvM/jO01AswkWLIBaAZ5+1eOkli9ZWhU98QqUtdmyxYtuwfb+Tsp0zidPM5z43kdY8wySTJv/xH0PE4xYXXODngx+cpKDMxeU9go37AWIyJuYQ/gfwpJRyz8nu5wosl3MfKZGjo2AYyJHhY262sBz6MtAcOiyugInBx4dZ0QZVIbh5Nlze4NghAMTOYHR8Wj3cdhn86vsmKAIhFAQgLZvSJEMPL73Uy3XX5Xj11QKqCs3NBtdf7ycWU4mnIPoWo/nyco2vfa2cYlHyyismL71kYpqSQgGCQYGhQ2sszxe+E2d83GlF/PKXSyjKGK1NZezudqJ9ra0evv61AGtey9PZaTOcNog06shpJZ5bNUAsEqazw2ZsMMeNN/l5aquPntEqSEokSYZHUvzbX6fYua2KpcvCGIZCfhS27YZVq2zq6wUHD0qGh6H+OF6aezrgp084a/rCh5ymgyPxvUNOBj09RcbHTZqbPWzYkOW228rQNPdNyOW9hx+FCzgHzAHPQYQQtwF/DxhAqxBiMfB/pJS3HW8/V2C5nPMIRUH96Mext29FPW/JMbeLeODuGUffXxdyzC1TBWdEy1gWKgNwSf1hcXUyHOyEXz1+uCD9kJ3CybJiOcyY5WHXtgxg4ffZLL/cQzT65jdsKSU9PZJ77w1z440WPh/MmqVTWany8POwbjt88tajIzuaJtA0wfLlOiMjkv37LS66SGPJEudpvn9/kUTi0FPeBDT+5m+SbN1Rxh/9AMZT8LU7BLPuKOeJWUmefibJrmGJJ5TCUFTaZiuMD3mw8iXiI1lW/q5Ab2+NM3CQISALeEGavPhoO527AnzxD9ooGBr7O+DiiwWvvmrT0CCoOEEK1ucFQ3cElvcdiFQdi7o6g1BIpaurwMKFfldcubxnySBZR+5sL+Nc5c+BC4GXAKSUm4UQJ3wHOGMCSwjhxclTeibO8ysp5Z8Lp4jhL4EP4eQf/l1K+c9nah0u7w2UpmaUpubT2rfMD793Pjy0HTrjUBWAu+eD/xTeuG0bHvi1Y+ypafDgb+BPv+J8f7JUlMNDDwT4228JeruKXH2Vzle+HEB5i0fBs8+WeOEFk1LJRNcFX/uan8rKk58R5vUK7r336LquefN0fD6LTAacp6RNNGrj98LMBhhJwpYO2NqpMa3NR1NjlsVLvTy7z6C3t0gx4SHmhYAxTijoY3hYQ5QUJAA5eKNA1gsotB9I8MAvx1iwpIpLlsCKi1UuvVQlGIScKXhhFyRyMLsaFtU5RfuHaKmD37/H6QatPMGA7jNJNKrx1a/WkEhYVFefRjW+i8u7COsd6iIUQjQCPwGqcbppviul/KeJmX+/BFqADuDDUsrxCd3wT8BNOJ/kPnnI5FMI8Qngf0wc+i+llD+euH8J8CMcT5knga9KKeWxznGCJZeklIm31GDKE13nmYxgFYCrpJRpIYQOvCKEeAqYAzQCs6WUthBi6trGXFyOQUsM/vhyKFlOTfapYttOh2FZFBAwFj/CJP0UmDld4fv/fuwwvGVJnnwyx8aNQ+zfX0RVNSwrxt//fSVCCG5bLgmT5fXX8gx0Glx2WRBdP/yk7yCFhWTaJN1Aixb5+Jd/8fGFLyQpFAShUJYf/agZXYMv3Ajr98GTrzuDpds7nBRmd2eeri1FFNsm7/WSzdqYpqS62kcqpYFqMjas4BiPHnpAJGAgbcnoqM1YBmZNd8b7RKOQL8H31jqRRL8Om3ohW4RL3vJ5cKobDU6XQEAlEHj/DMEdGSkQDGp4ve+fa3aBAAoX8g6NsXBC6P9NSrlRCBECXhdCPAd8EnheSvk3Qoj/Dvx34E+AG4EZE7eLcArML5oQS3+OYwIqJ47z6IRg+nfgs8BaHIF1A/DUxDEnO8fx2CGEuBdQhRAzgK8Ar53oIs+YwJJSSiA98aM+cZM4lfj3Sintie2GztQaXFzeyumIK3AiVbdcA489B0i46eozU2StKLBjxxi7d1tomkE6bfPII0k+//kI06d7eOWVNL97NkFZmcb27TnicYs77ogCUMDiOXqQQA0+AhwdcfnUp8r5+MdjDA2VKCvT8XicT6xBHzSUS6ySJJlVmN2m8tizRdavL1BAIdbgp6nSor4syNhYFdu3D+HxmPg9CcaVCNJ2ImITjxaQwRvQueLGKNNnQPgITdkTh5EMNE9EpgIGrDp4tMByeedZtWqIp57qp7zcwxe/OB2fz60ieb+QwWYt+XfkXFLKfqB/4vuUEGIXUA/cDlwxsdmPcVJyfzJx/08mdMUaIURUCFE7se1zUsoxgAmRdoMQ4iUgLKVcM3H/T4AP4AisY53jePw+8Gc4gaMHgWeAvzjRdZ7RZ48QQsWZQj0d+Dcp5VohxDTgbiHEHcAw8BUp5b5J9r0fuB+gqWmS8SkuLschi003JtWoRCcZEP1WCiV4aiMcGICWKrjp/Df7NoEzjHneLMewNHSGakEtC+rrJRs3CjRNEgg4lgpDQzbTp8O2bTlqagwCAYVwWGXLluwbAsuDykVUYSHxH+epraoKtbVvvjjblqx5YYzstjznXRTmtqV+XvipQmurgc8nqKyCxgbo6RkjFNI477wgc+ZIensNNm602LFDJZ12vC88ngwNTRp/8VdNzFvkpa4SAkcUpSuK8xi+cc3SHQB9rrB/fxrDUBkeLpBIlFyB9T5CIqYyRVghhNhwxM/flVJ+d7INhRAtwHk4kabqCfEFMICTQgRHfHUfsVvPxH3Hu79nkvs5zjmOx9yJmzZxux24DWdkzjE5o88eKaUFLBZCRIHfTNjLe4C8lPICIcQHgR8Al0+y73eB7wJccMEFJ8x1urgcya9I002JMCr3E8FzgvbjpzfBun1QE4WNB8Gy4cOXHr1dMHD0fVOJpgmuuirEli1JkskSUsLs2X4aGpxoVGWlxu7deQIBg/Fxi8rKN0epFnJ6NgLZrM2uXXlaG1RSA1mi4SC1tToHD1qYpo3HEPT0mGgaXHihTjqtommC224Ls29fgnAYyisM4nGbUMjDt75Vy223KExmG9UYhZYyaB8FjwZ5E+4977SW7TLFXHddDU880UdLS4Dq6jPgV+JyzhJA4SKmpj332zAipbzgRNsJIYLAw8AfSCmTR9Y4TdRLndH3/lM4xwPAHwHbORyqPyHvyMcTKWVcCPEiTg60B/j1xK9+A/zwnViDy/uLOBZ+FDLYmMgTCqyDA45hp9eA2qgTyXq7DDHGEKNMoxEfJ/9mde+95RiGypNP5olEdO65J0RTk/NUnT8/RHu7RVdXgVhM40Mfir79hQLBoMoVV4TYtCnL9deH0DTBn/xJFV//+hAvvZSmoyNFLKazeLGfUkmSSFjMnGnQ1wdNTSr790sqK0FVBOXlcNst4k3iqjgxAckwnDTtJ5bC5l5IF6CtHFpde6lzgvp6P/ffP/1sL8PlLJDBZrUsvGPnm6jNfhh4QEp5SBMMCiFqpZT9EynAQyVEvTi124domLivl8PpvkP3vzRxf8Mk2x/vHMdjWEr52Elf3ARnsouwEqfyPi6E8AHXAn8L/Ba4EmgHVuCMQnNxmVI+SIgN5JmNTuAkwt4t1bBhH9TGoD8OC0+vYfFNbGYXKTJoaMzm5AuMdF3hIx8p4yMfcSwbDn2qy+UkP/+5hdcb4s/+zMDjEUd1IJ4O3d151q9PEY2q/MEfVL1Rl9XeLlm7tkB/fw4hIB4vYNsWjY0qjY0Gt9wSYvVqSUWFl5aWAl1dRUxT8KGPlPEfvxAoCnzgamdk0b/+q9MU8JWvOCLLo8FFU/AYu7i4TA0SgbTfsS5CAXwf2CWl/IcjfvUo8Angbya+PnLE/V8WQvwCp8g9MSGQngH+WghxqNf4OuAbUsoxIURSCHExTurx48C/nOAcx+PPJ0blPI9ThwXAEcJwUs5kBKsW+PFEHZYCPCSlfFwI8QrwgBDiD3GK4D9zBtfg8j6lAY2GUzDNu/E8Jy14oB8WtcAtJwxun5g2GulmgJrTTNvt2gUNDYLQhKmozye46SYNnw98vql5IRwbK/G97/WjaYJMxmJszOSuu6qwLMmvfmUyNJRBVQW6rgCSkZEi99wTYfZsL+vXF9i5s4imaSxbFmPBApPzz1cZsgzGk06d1UNPwxfucequXFxczl2CCC5m8jFkp8p3TrzJpcB9wDYhxOaJ+/4UR/Q8JIT4NNAJfHjid0/iWDTsx7Fp+BTAhJD6C2D9xHb/51DBO/BFDts0PDVx4zjnOB6fAmZzdLv02RFYUsqtOIVrb70/Dtx8ps7r4nI6eA24a9nUHnM6TUzn9Bs00mkoFHhDYAFcdtnUPmVHRkpYlqS+3kOhYHPggGM0aNugqgJNUyiVTIpFgW3blEoqL79cpKZG56GHssTjBYaHbT71qTCXXOKnokLwV/8hCPqdY+QKTgfml7/snO+tvmGvrYFNW+GC8+CipVN6aS4uLqdAWkpetScZK3EGkFK+Ases27h6ku0l8KVjHOsHOLXcb71/A3DUkFsp5ehk5zgBS6WUs05xn3fIVczF5V2ElLAvCZvHof8Exsan44V1sixdygkdz98u1dUGHo9Cd3eBnp4C8+c7Vfy6LqisBL+/jFJJwTQtbFshnYnwd38Pv/tdkd270+zYkSebNVm5MsmWLRmEENx5HSTSkMrCHRMvY85w6Tefe3AIHn8Gcnl45EkYGT2z1+ri4nJsJALbUqbk9h7kNSHE3FPdye3BdXF5C4/1wuoROFTe9LEWmBN58zaWBY88Cxu3QW01fPQDEH3LNlLC+jisiTvHuqIM5p/BeYenQySi8bnP1bFtW5pIRGPxYietunevyeCgydy5Ptrb60GxQdFBDXCwR+Ff/iVN2wKVWfM91FUKfD7Byy9nuPLKIHOmCf7H553jq8dxyNA1J3WYyzlfteNsm8rAum3O9xcugNAR3Zy2fWZSkOPjFoODFj6fQlOTipisJdLF5T1CEMElytSY+x0VTnr3czGwWQjRjlODJXACa2fPpsHF5d3GSB7WjEBzwBFFSdPm8V7BnMib31x37Ye1m6C1EQaG4emX4Z63jP3clISHB6HGgKKEn/XBpxWYcY7NU62qMrj66rI33bd2bYlIRJDJ2CACTmW6LZ2qA0Wws12lMF1QU6HS4gOQSHnY3+p4wuoQZWVw3z2wfQcsmA/R6OTb7dsPf/XPkDOhqRV27ocv3QupNPzkNzA0Cjcsh0tPs27uQCc8/LRzebddDXNnQGenyQ9/mMI0HXf9Sy7xcsstPldkubxnSUvJKyXzbC/jXOWG09nJFVguLkdgSmcmXlEU6GSAjFKkYHoZI0LZEeNnSiUnaiIUULwQzx59rI0JqNAhMPEsy1uwLX3uCazJyOcdg9PKysktYgy/hj+iMjpYYtRQyCVNli8PnvIw5FkznNuR9A+CrkNFGfzuVfjH70NfP1QHoV86ka9MDtZthcERqK2Cp16CRXNO3acsX4Cf/dbZz1DgF4/B1++HRx/Npp5weQAAjrdJREFUEAgoRCIKti1ZvTrPkiUGdXXuS6bLexTJezW997aRUnaezn7uq4WLyxFUeKDeb/NqZgSvDoVChMW1o6ylmyu5AC9OCH1mG4zXwJM2pMugrga2bYd7auDyibopj3rY/wmgJMH7Drx+DQw4dU011eA7Td/ARYs0fvObAosWafz61ymsUhkcmnloWcyoN/nQLWGsgQLBosWMFX4uvvjtu7BaFnznAYhF4AM3wY+fcLyycgqkLEh2wpKljjN8wAclExLJCX+tY7ya2bbktdckBw9Kli0TzJhx+I9QKDgzJoN+R1gPjzmPXSolCYed7RwrDEEu5/odu7x3CQjBpacyvf44/GRKjvLuxxVYLi5HoClwV2ue4aExrEKYhqo4c8qLJLBIk31DYP1q3GbVNJvkOBRM6M5ASdHYHIdvzoQbqpyaq//shp68k37yKnBh9Myu/7nn4cWXQVEhEobPfBLCYYmqnlpkafFine3bTV5/3SQUyhCPK2AZaIbA67GIBItUxxU+eG/khMeKJ2FfJ9RVQf0JhlKoKnzwRvB5YTwJfp/zIhXVIZMFwwdDSfjtCzCrDhpigAq33wCeY3SY79sHjz0micXgZz+z+eM/FgQCzuMRDsGCWbBll7NtdZnF/n1FyitUHvqtgo3Kpi5BIuvh//0SPnS1xb/+nUosetIPpYvLu4K0hFXFM9i18z7EFVgu71uy2CSwiKLiO6KhNqJpLKkbJ4yJioKNxEaiTzxdeko2fzdWolezUMsziKwkNaRRTBtU1Uv+rk/l6iofjT7BF5thRwo0AQtCUHYGBkQfYmQEXlzpzAxUVTjYYfOn30xRFkkzbZqHu++OEQicuDiqWJT84z9mefTRNJmMRNcFzc05fD6LsXEoFIvs3q/R2X3iiI5tww9+DUNjYOjwB/dBWfT4+yyc43yNp6AyInl+m81QPwghuO4WQWOt4LlX4ccHYX6Dk6o1jnNZpYnOc5/Psb6wrMO/EwI+dBOcPw9SGZtHfhXnV7skz6/1UBQG+7oVrHEbNElJ2Dz4qEJnr8VTv1DfZJ/h4vKuR4K0T6J40uWkcROuLu9L+ujnP9nCg+znB4wwwuHiTg8Gc2gjTooxEoyToI06IhPGpS/nTJKmBGmiF0yy3X5MTaLOGaEQzNCpJvhhZhwbSY0Hrq6AFeVHi6uSBXvGYPMQjJ3ADuJkKJUcwXCowLyjI8/goEVzs4f29gK/+13qpI7zuc8l+dM/TbJ6tWT7dpN02iaZNLHsApZdJBySeD0KHt+J1aJlORGsiqizvmz+5K8nEpT4UjZ+xfkkWEjDi09IBntBs2E8C/UNjojr6Tn2cWbPhosvds5/++0K4fCbo3mq6qR8m2pszJJNQaqkkhCLqFgF6YQ1hXBm/NiSDdvgR784+esoFGxGRooU3eiAyzmNAGuKbi6AG8FyeR8yzOs8zkrSBKlGkGYhqzG4legb20yjgRhhsuTwYFBBFBubPoYZULuYVV2gezzGaLaMUlAj0ByHogro6ClYnyzwgYBJFfqka8iW4PvboT8NCKfn955ZsKDy9K+rshLqa6GrG7xeGBuVnL/IeVMPhVRGR0/cIZTJSB54oIBlOSajUnoolWw8HhNdc2qdNF1j+qwgl106+bUdia7DXdfDS+vgyotOnCI8klwO0mmJpigUc07as1iEtSvhghVO/dVAv9O5WH2c42qa4I47TvzJvLJS47rrAvzm8QLzL9DpbFcc9eaTUK04raBjIITk9a0nXr+UkpUr47zwwtiEcStce205l1wSeU91Ix45zsnl3UtQwHLP1MRcHpiSo7z7cQWWy/uKUXro5gkK6KTwABlgD5IZR21bRviNzkGJZBt76aKfOs2HV2hURoYp14bZIReQJ0BYFPFLUCWYBcfR4FisH4D+DLRMlDDlTPjNAZhd5gRKTgdNg0/eB6vXQSoJs2cK1q8t0NsrKBQk1113YhOuREJiWTaK4sw5dNJpBpGIwte+Fqa8QiMQNGht1ZjednLrWjjLuZ0qHg8Eg86ooMZG6BuEUNTp/Etm4NN3Q1MZzJjh/P7tYNuwYQfkVD9f/7qfVZvhkadh14CkNFuAiuPbMQzePsGCOSc+5ubNKZ58coSmJg+6rlAs2jz66DCRiMr8+e/+/KJpSh5+2GbbNrjwQrjlFmVKZmO6nB3SNqycpBva5fRxBZbL+4ohOjHxMpMtdLOccXzo5GhiDIgdc784SboZoIwoZYYgLItUGIMI7ziKx2LN4ApsUqhaASNoM8+rU3Gcp1dnEiJHZNh8GgxnIVmE8tPs/APw++HqK974iXlzBH19JZqaDGbM8J5w/7Iygc+vkklbFEtMqESLwSGbBx8s8s1vepm9UMO0z5zB5yFUVXDffQqrVknq6iRt0wXhCkEqDXdcAysunLrzb9oND//OGZm0dS/8t0/AB5ZDPqTzxDYTMwUoAr0Ozq9W+NzHT3zMVaviVFXpE3McwTAUKip0XnklccYF1uBghmSyiM+nUVcXPCPC5+BB2LwZmppgzRo4/3xoaJjy07i8k9iuQJ5KXIHl8r5CQ2eIAFGi3MHLjBLEx3IKdALTjrnfMOOoqAgEUkjOD21kXA5QVARN/k66xxvp7qzH8OT56KyNnF9hsYcaZnI+2iRpwtYI7B6D2ITmyZng1SA8xUXwc+b4mDPn5BSbaUp+8QuLq28I8MRjSazCIYVVIp9XeOHlLD0Dkpu/VI7Hr7B0JnzwksP7S8kbqbDTxZ4Qboe6xZuaBP/8z/CDH4iJ4wpuv92JmLyVkRGb/n6L+nqVsrJTU17xlGPzUFMBPUNO+tHng09+FMq3aiT6IVeCSA38220QPAkvs3TaIhx+84NhGIJ0+syZOQ4NZfn1r/fR3Z1CUQS2LSkr83LHHdNpa4tO6bl8EwazY2MCRZF4T6zfXc5hggosfxsf7o7ETRE6uALL5X1FHbPYyyYGaENDwUOYILWIiX4Pic0YB8gwjI8Y5cxEOSSs3kj6FWn0jNCej2CbMN4Xw9hUJCbHqajrpMzvpVzzMMYg3eyllXlHreOCatg+Ah0Jp35aEfCR2aefHpwK2tsle/ZIbr7WYPGCGA8/lGXv3gwlW0VRVWzbpuNgCcOyaK5SWLsbzm+BSAjWbpL85/eK9PcWmTkNvvnfPYy3ZdlInDYCXEEF2jFnuzoMDMCPf+LYMdz5QVg0MYRi5kzBN77hdEmGw06t2VsZH7f59rez5PMSv1/w+7/vJxI5eZF1/hzYsgd6BuGaix2bCIArW6A9DaN1zs8fmAaxkww+zZ8fYMOGFA0Nh/0jhodLXHZZ9KTXdSqMjeX4zne2oqqC5ubD6eBkssj3v7+dz31uIU1NUzerqbFRcM89Cnv3ShYuVKiocKMf72bSFqxMn+1VvLdwBZbL+4oAES7gJjayEg8GXiJkyTKbxQD0s5lBtiGxMSmQZZRmLqOKMvbQgY2NQCOmaQSNFAiTDTuXUVY2SlhNkBs06EvY5MoFHt1Hmvik6/Dp8NmFjsDKmdAUhsgxfJzeKZzB1RIQRIIKgYBOIKCTSBeRUqJiY3h0ulOCzq0wOgSf3Q5rD9ikeuPQaUEaVq9ReWg11P/zEAGfTps/SXs6yEcW+wj6j33+Va84RewV5fDoo4cFFkAk4tyOxfCwTaEgaWlR6ey0GB62T0lgxcLwBx8D03LsJN44rwe+tNhJ3/r1wxHHk2HFijL27cvR0ZHD51PJ520qKw0uvTR68gc5BVav7sc0Laqr36wAw2ED07R5+ukO7r//uKPTTplFixQWLZrSQ7qcTdxG1ynFFVgu7zuqaWQZ19NNOzYW02mkinokNiPsJk+KLGOYFBi3+1lpjhK3ymjVK4lrQxgYqMoiqtWVpJUSZlBhdKgKRbWo9o/iCfVSsGsRpKmh+Zjr0BSYfuyyr3eEVAoeeQT2tsOQJWjvUNjRbjO7CebMUQmFDDZvtshmLVSPTvQiP+ujKukRaKiALfssSrkcxP3OtOZwEbIZTG+erCiR99iMphTs3ymUeuH+Ow6n/95KWRmkM1AoQkP9qV1HXZ1CLKbQ2WlRXq5QV3fqoUBFccblvBVDhfrTKJmKRDS++MUGdu7MMDBQoK7Ow5w5AbzeqQ9TSilZt26AqqrJ3fRjMQ+dnUni8TzRqJvLczmaoALL3/4wBsBNER7CFVgu70uiVBCl4i33OimOLGOUKJAjTYe0edm0yWlxSqbFx+0KFmglSvl9LC6p/EqtJ3BeltDWJEYJFs/I4fHm8RklqphFxJxG3IaI7qQCzzUeeQT27oXdCegbEVy8RCWeVJg2B/7sJo2VKwWPPKLSMQpD9Rrl13splQRpA9YPAQio8UMSpyGz5AEpkNk0uS0qWrlNYb2fx38pSF4juf4iwbSmydey/HKnczCbhYsvOrXrCAYVvvQlP8PDNlVVCl7vufFg+3wqS5ZMXVruWNi2xDTtNwrq34oQTleoabrjflwmJ23ByuTZXsV7C1dgubhMIBDUs5Rh9pJlmA5q2EYNI7qPwVIVedvDD8QoDyReoNE06fDFuNoeYZ1tM31eH0ZREhRVLAo0caG4htWj8L0Bp/h7QQTuqneiVucSvb1OTdPGUYj5oVAQzJwt8EadlNytt3q5/kYPf7MX+jKCnrSzz0gCOAjkAAtoBdqlMzQQD+YBjdR34ihhSWmrjrSL7Nqk8szLKl+8b/K16DpcdunpX4vPJ2hqOr3oUKkkefnlNMPDJpdeGqCp6Qxa7p8BVFWhutpPMlkgHD4611wsWqiqIDzVXRQu7y2sE2/icvK4AsvF5QjKmcESPs1efsdOUsiSh458EyqS31N/wvzsNkbzI9T7PkJpsI8tvWCNF5g2r0RDrIAe2kGD53riRXh8AOq8zpiczQmYH4b5Jx7d946yeDG88AL4JXSlYVYQRhNwxeLD2xSkoChhVgSGsjBWxPG9L9rOK4iJU7qlCiiBEwnUMPfUgz0GlEArYAqDoUEFTlDsfjZ49dUMzz2XJhxW2Lu3wNe/XoXff46p4ROwYkUjDz64i2DQOMqWoa8vwxVXNGAcb6aQy/uaoALLp8g9xE0ROrgCy8XlLURp5Dw+ygF+xTYZplYf4PPad5gl92KkJVIxSZiv8cIWHwc7pxNZXGIgU8KuK3JBdoiQsZesXQQMDmVsFCB3jn06zGZtIpES06YJ5nhUlJiK4oVZjXDB7MPb+TUIqE6N0gUxGAC6LaAc6OWwwMoccXArAxSBiXofaVJIJ/AbYWBqqvntiYLcqfDCGh+3CAQE5eUqXV0l8nn7XSewFiyoYNmyOtas6SMc9hAM6uTzFmNjeWbNirFihWtS5XJs0hasTJztVby3cAWWi8skCARNxPAS4Br9OQIii2bZBGQWKQT9jFPXOkxhwxwOPB9h0Ye6sQoqA0WT6eYavPo4YZ+PbRmVkPDiU1WmnYR30jtFNmvzne9kGBqyUVVn1MmnPx2gpeXolwRVwA018Mse0G1HHmkqlMJAAkgDm3BUpAcwi2AVcfKHh4Ys+oj6vLz8XIJrL49x3nknHrNzPHbuhP962BFZt90KS85/W4dj2TI/u3cX6O4usWyZn1js3RfpURTBbbdNY968ctas6WdoKEss5uHGG1uYM6cc7VzLT7uce7hdhFOKK7BcXCZBQ2chF3OtOsBmaRAnwgBVRNQDFIshhJJmeFobTV8roJlZlLIAxbxJSoR4XY3gUTYwqzmAlghgWAHuDM+gzHh7omIq2bmzxNCQTWurIyTGx22eey7PZz87uQo8LwpBDVYOwwYvBEYgvlNx0oQdwAjOi3MVoBacfGMpD6gYBphWmoEDRYpxjU9/doRv/X2EK6/0IyXsy8LrSSjYsCgEC4LHr1XL5+GX/wVlMcfU9De/henTjm/jcCJqanT+23+roFCQhELvPnF1CEURzJgRY8aMs9ye6vKuI6jC8inqx3BThA6uwHJxOQYhYnzMiJEo3Muw/D6W4qHLdwEftZL0ie30eupoLPYze3AfSrfNULSC7ZWzMcwMzfYgYWMeNWUq4wySIwDHsWw4HUzTERin051YLIKqHu4oMwzI54/fYTYjCNMDMLARhgqwrQSlrAIlCUEgKZ0QV8oECoCG0BSEsLEtBdsqMDhgks1a/OpXCq2tOgdCOs+NQlhzImW/HIDtQbi31vn5WNdtmk7HoRBOFKtYPPXH4K0YhoLh1oBPGbbtdKhWV0PM1XvnPGkTVo6f7VW8t3AFlovLCfiSZxrF0n0ohV+iKSXwV1HIlBHLJ1m4fxumJkiHA1TlB7k+PkilVUFQjCG13QxHb0dVVIpO9feUsW4dPPYYVFTAJz956tGbadM0FEUwPGzR0ZHj9ddLNDcblJfr3Hqrl9Axil1HUk4t2cevhid8sHINFGIC+gGvgH7bSRXaIDQFryExSzZOYbuNEAqFvMmqVSVu+VCJV+t1mn2HxVRMh50ZaM9Bgw6PbYH1+0FYMKsWrpgHbdWw7GJ4bbWzz+JFzuMwVVg2JIomeAeIUovCuzeidTbp7oZvfxuWLoX7jtE56nKO4aYIpxRXYLm4nAgpMYq/AiUK+EDroCL2eS7p+y62J8eBhiZSIkRjqR+vUsAyFEZEkVipB392LUPBRZSRJsWvMJiLh7lvdzk8/rgTGejtdeqRli07tWNUV6t8+tMB/uqvx3no1zqFgpcdu+GFFzJs2iT4+7+fvBBdTJzf54W7roK5TfDMKujSwWoHFBVFCWBq41SU2xi6YHgYSiUbRbFRVQW/XzA+bjGYEW80Hx6JR8C+NPx/L8DrByDgA12BUhH29sFHL4ebb3KElW07A4ZPNoo3Ng7f+SkcaIerL4XbboTAW8wVR3MwlBE0eM/Njsd3CzU1cNNNMHPm2V6Jy8kQVGF5dGqO5aYIHVyB5eJyQiRIE8Rht1Aj00kzVTzdFmSLmMlz+RV8eOw3DFkVqAGbC2N7aFMHUMx2FnEPBr/ARKXEAXRaUDjOzJgTIAQ0NcG+fc73pxu9qa5WefI5nWQ8BTIFKJRKPp580jimwCoPQX0MhpJQFYa506GuBroH4eaZYOYE9TVeXnihjH/79ijj4zaKaqOqJkIY+HwCkESjKvPn6uybZO6xKaFzEDYddKJVXTvg9ZckK0dsYlFIDSv801cEDafYFCcl/PH/go3bwAjAC6/Dr1fBP/0Z1FUd3q4qAFUBFag7tRMcg3jcYu3aPD6f4OKLfRjG+0O0eTxwww1nexUuJ0vahJWjZ3sV7y1cgeXiciKEAsaNUHwUECAaId1Be2wOe7UMLyYu5cDrs9gXnk1zsAMzo7GfSsr8capiUWooJ0cFJt0olCFwit3TjDHAAXR81DMTjZMvALr3Xqe+JRyGtrbTu6z1r0tGhwpgjyCUElIqSKuErkcxzclH2ggBdy+Dn70CnSPOz14d/vB2Rwwdora5jP35AB07UuzekiGg2YwO2VgWBAIa/+N/RDm/RWN1F/QXoMZwjjVWAGGDlnZiR6lh2P2apDBoU8zBQAp++k82X/yAwrzWUxMqGzbCi6tAqM6IoGgIeobgXx+Cv/7y6T2GJ0JKyU9+kmR42KJUgnjc5rbbzqF2UheXI3FThFOKK7BcXE4G42LQ2kDmQNSA+Bs0KRmkhlg6gW0bbAwt4srY8/hkjpKi0hUIMeLNkSw9TbNyAZXqRRjUIdApkmMnryAQmJQokGEmJz8fxu93TELfDsWixO+X5LMSUBGKgrRs6ustTNM+Zlt/eQh+/3roGwfThroYGG95JUmkIVbt4bxFHvZfGqNWz2El8/h8Klde6WfuXCdCdl8dPDzo1FwNxaGzF2b6nY5FgNFhsC2wTImmKwigkLXp6oV5rZNf1/AIWBZUVjhNAIfYshWiARjOQGIcwl5HZPUOv62H8bhYFgwNWdTXa6TTNr29k4TsXFzOAYIqLC+bmmO5KUIHV2C5uJwsyhF5pLIbmDX6G+qjCrsKddRWdrO85SV2iWnolo2qmZTpoxzsi7HRtonoW7m2rJmlvhkAFMhiYxGiDAuTFO98bH7BPMG8BX7WvOahVMiALVA1laYmi+9+N85nPxvF55tcZCkKNJQf+9hN1VBTBl2DEImofOyWIJXRoyM3UR0+3QBDefj7Lsdvy6vC3hGYUQmDJdC94IsIsiMSKSFaL1g0SV2PlPD4U7B6HezbL+nvsfjYPQr336+gKDB3NkgLCiknOpewYKAAH73Q2d+2oafncF3XoQhef79JZ6dJMKgwZ46Oeqz2xknQNMHll/tYuTKHosDNN0/RNF0XlykmbTo2LC5ThyuwXFxOh/BF+PRyvpzfS7Isyz5tJ7YUjJoV1Ad7qZRD9KZnstFYSCYfQxQ9JMe6mFM/SohKfITx4CfJCBJJPbNPfM4ppqpK4d//OcDX/qiKDRsSWGaJyy4tcd55Gu3tJdrbS29Emk4Vnwc+f6sTlYoFnUL14xFSwRCOuFIE+A1Ythhe94BnqaBjj8JwOege+NY3oa7qaJHT1Q2vrQNNkax8MUMuZ/Hne2D69ADXXKOxYL6TTs0VQc+DrwE+dAN89CZHnP32t7B+vZOqnDkTPvYx6O4u8f3vpwFnXuF55xncfXcAcQreGNdfH2DJEi+67ohNF5dzlnNs2sS7HVdgubicLr7pxHzT+Z/eEv+vczW7+yUVbd14QyWq8fO7wlzaD7RSGg8w1h5lh9rERbePc0dbJZrQmccKEgyiohOj5qxcwrx5Kr/8eZjvfGeQp56KM3duPbYtkVKi62+vGNvQoaHy5Lb16dDid2q7bBuWToPbV8CFzbC2DfZ3CqpCcO0F0HKM2vN8AVQF4uM2tmVheFRs22L//hLXXKORy8OsOXDFFdDXD/V18KWPOPsODcHrr0NzsxOd27MHurrglVfyqKogm5X096fo7ITLLzeorz81w6yKircnrNJpm1WrCiQSNvPn68yf7xp2uUwtQQ2Wn+Tz9US4KUIHV2C5uLwNsln4wU910kMX4KGT3U83sSEjSA5VkWj0kA9rjK+tAARYcOfvKlj+lSF+eIOHVsJUTrH56OkQjXr4oz+ayy235Hn44Qzd3SYXX+xj2rTJnefHC7B73HFbn18Gvil4FYlnoKsHrmh1IlipLLQPwew6aKkCLjvxMeprwR+AQlEhFlMYj1vMnyu59FJH3FSUw/w5sH0XaDpcf+XhfYVwolhw+KsQYFmCdesU+vpGSaVyhEIWq1f7uOuuKqaSwUFH2FVO8gZXKkl+9KMMg4M2fr9g06YSH/kILF7siiyXqSNdgpWDZ3sV7y1cgeXi8jbYuhMGh2FWs5/q5CyeeNAmL4t4g0VKQx5SGNAiwA+owKhgzS80/mlZO1+INDObc8PiWlUV5s3zM2uWb6L4ffLaq7E8/PtOyJpgS1g3BJ+dA8bbzHwlJkYW1k8YplomDCcdgXWyBINw/yfh1TWCOTMDhAMm5y1WmDbNeZlTFLj7A3DlpU6TQPgIM9XKSrj0Unj1VefnRYucaNZ553n4wQ9yWJaFZUkCARWP5/Qje5Ylef75Ert3W8yYoXLttTrrXxc89qTTNXnnHXDeIli/GV54xVnj5Utt+vttmpudB1lVYcOGoiuwXKYeN0U4pbgCy8XlbVAoHC6GHhlV8GgKCoKKqhxdvYrjbm7jTI4BCEFxKMjeoXG6wzFmi3NDYB1C0wSadmwBsTPuiKvmCXHSmYKeDLS9zRlm5UHQNRhLOx2JhRLUH6ejSUoYTjsir8wLew6C3wfTmuH2m8Gxkz9agCgK1FQfdTcAN98MF1zgpCirq51t58/XuO02L5s3V9HXN8Ytt+isWHH6f7PNm02ef75EdbXC44+b6Lpg516NTNpiyxaLBx+U5AoCS9W4/FKFeQsEv33G8Q6zLImqCvJ5STjsCOCRURgdg1gUqqYovePy/iSowfIpCsy6KUIHV2C5uLwNZkyDZ1+C8TiMDUFmCDxBlfhgBCGl8x6v4bzfC8AERbNQvUnKzJWgfgCUY8ylOQcxFEfUgCNybI49M/BUCHrh95bDk1sgX4R7lkHbMV7sh1Lwi00wmHLSeOMjYHZCmQe+dB+Ul8G6jTA26oiO8xY4EauTofot4kvTBL//+zrd3RqRSIiqSYrrTRv2Z6AzC5UGzAmD7xgRvfFxiWEItm5V2bJFsmqVSXVtgf2dKp39GhIFbAESHnlCsnsv3Hijwg1XeHnxxQKqKgkGFa66ysOuPfDAQzg+uMA9d8KCeSd3necKXV15fv3rQS65JMqFF76Nad1TwOgoPPQQjI/Dddc5Yvv9RLoEKwfO9ireW7gCy8XlbVBXA5/5mJPO2VmEq5dDRzfUzdEItMGG9iIH89ob8/nIQPl5/dhhjenJHyLFPkT4ftBO0Zb8LDG/DNYMwtZxKEq4sAIap8g3s6EM7r/y+NuULPjRekfUNE9EuEaHYEcBLjJgbw/896/Crl2Or8+yBbDiUrj/E+A7QSfjsfB6BTNmTK4iLQk/74adKacDsmBB5Qh8pgVCk5SwzZun8dRTFq+/LhkaMikr02g/YDOSzCO9ISfiCZABOw8dPZJiRnDttV4WLNDJ5STV1Qp+v8L3fuKIyYAf8nn47eMwf+6bxwaNj0tWr3byPhdfrFJWdm65yO/cmWbv3izAWRdYjz4Kw8MQjcJvfuN0nJZNkS/UuwY3RTiluALLxeVt0toMn26G61c4A5hnz4bmefC9l6BuRo5/XKvCPsfuQJ+bIvsRLx1WPT4tBrYG+VcgeM/ZvYiTxKdCbRXsVBxbhU4DOvPQeoR4iWfgl686Tu/nt8JtFzgdhVNB55hTr9V8xBvfwulOBvaKufD0Wti306ldKknY2+EUv+/cA0sWT80ajuRA2hFXrUfYW3VlYe04XDNJBK62VuH663WeeELi8WjYtiCeUjBLAqICihMb+iWk8/h0jULR+d+pqXlzWKxQhNCEuNV1KJacqOIhgZXPS773PZO04zLBtm0mX/2qhtd77oisZcuiAMyde/bd7VNp6B2Cp1+yOLCvwNq1Jv/wDz4WLpyif95znKAGy6eomdlNETq4AsvF5W1i25LOzjSrVw8zOppi1SrJ3r0+DKOaPeN+greOIZuzCK9jdImi02j1IZSlCJkC8e5JEXYWYGMWFscmuv1M+K9h+OOmw9s8+Ao8thUG0/DIdqem6ralU3P+/CRG6KoKtZXOcGENQHHmGSLBowPCsXA4E3TnnLTpkcR0R3hNJrAAdu0SXHON5OWXJbGYjS9ksf+g5qSQDx0rO4Yi0iglQSRYA3iPOs6KS+GpZ530ZzYH11zh1I0dYmwMkklobHQEVXe3ZGSEU57heCaJRDRuuOE0h2lOMTNmwY8eggN7i+RLFq+uL/GhD5XYujWGxzN508d7iXQJVvad7VW8t3AFlovL2yCfN3nooQ527YoTDOrEYgZCQDxeIDO2n0jJxzRZxy6/jV5lInRBQJb4SNpGi+RAnwG+K6Z8XaWSZO1ak/FxyeLFKo2NU2NwmbWcZkhlIggSVKG74NRlHbrv1QNQtKA7CTkLfrFh6gTWoS5D03ZsIiwJ+004IOBCATfeCA+thfEE1OQh0AIHQrDGhGwXLK6AytOfs30UlQaU3jK/LWXCzOMEZEZHYd48hWhUsnt3iUhRQTM0SkHY1w22CZ5igWi9gaTE0vOLTCqwLnPGAfX2OYX78+e++feRiBPZGhuTCOE0Y0Sjb/uS37P4A7BwAQwPSMy4hVCc2ZHj45Kas2NT987jpginFFdgubicJrYteeihDvbuTdLa+uYoVCzmIRbzEBnKU13q5kO0cXAgiicgWBpRuK2+DmHccvRBOzdA5zqINsCc6x3rckDaNlaphOY5OWf1J54osWaNid8P69ebfPnLXqqq3v6n8GrDCbRkLPAr0FOAWf7D4gqgtQo6RsGvOULrwmPMDHwrpg37087XlgAEJ8nMxPxw7Sx4Zo/jv7VNQLcFjVH4t0EQFkQ+BqMDTrRtZBzqvPBsL7QX4MUeuLgabmp1BNrbZXYYar3QkYGY4YwbUQUsO84YoTlznEHdjY0alVUalikZHYMbblV4bqWgtxe6O2MM9Y2w4lKd66+dXBEKAfPmOLfJCAQEn/qUytNP29i25IYbVILBcyc9eK4xYxpUVEJVjUGuAEqpyFVXqFRXvz/c94M6LD8FW5Tj4aYIHVyB5eJymnR0pNm1K36UuDoSrcFg4/Q0VbWdXBaOcLevjugRwQiJpJ8MEknt+DjKll9DoAzaVzvias71JLq72fbAAxRTKcpmzGDe3Xejn6Bie9cui4YGgWEIurpsBgftKRFY5Tp8vBp+NQIjJZjpgzvekuH58jWQyENjCmbXwuevPvFxLRse7ISdSSdLFvXA56dBWH/zNutHYVCFBdOdIvBtabgiDDtKoErYkYXxIqS9EgRkVMHQEHAA1rbAzXMhX4I1B6FBgxlVcMUsxyLiEIUivLAJuoagpQauXHzsGjJDgU+3wIY47E3B3BBcXAblx9HBN9yg0Ndn8+Jrks5+aKiS/OU3FWbNElx2IQwMQaEYoKrcj8/HKY3leSuNjQqf/ex7P701FdTVwB9/Ga5drtHVqdBQa3DllSpv4+F/V5Euwsrus72K9xauwHJxOU3WrBkiOFmYZYIxS+P7LQH6PDUUn/HwhFliVczkT69N0FJh4aOanYywgX4ksNjKs1gA3jBYJUgNYVsWW3/6UxRdJ9LczOjevXS89BIzbrzxuGubMUPh9dctgkFnQHJl5am/yZZs2J10uuFajijinuGHbzQ56bnJLBpqovCteyBdgIjPGV9zIvrysDsFbROptc40bIvDpUd4Oz3WA2uGHdGVNaHcC9MroN8ukbVshilR9GbRTfBYAQqmByoUMAVkBYkueDIIFwUhVYTrq6B7NxRMuGURJLOO/9Yz62BnJ5SF4eUtzv0fWnHstfs1WF7h3CbDNCU9PSaaJmho0IjFBF/5isJf/hsE66CxAWbNch5IIaD2DauI98k7+zlEVSVcfzU4Mv99KEztE2/icvK4AsvF5TQ5eDBNLHZsN+31ZoC+UABvR5JbGh8jEkyya8+l/L+Vgj/+4AYquZABwvgxUBH0RTQWByphrBOEgmy9mFx+lGI2TbSpBQBvNEpm8MTzLG691SAWMxkZsVm6VKOm5tTfLF4YhN8Ngi7gizOg4S2ZquP5XxkalE3hq0uyCOtHoCV4OB25L20ja0bYS5xSIInIg68viFdXCMXiJPqiJLrLnDCTLkCFdBIOSJgVhXEJ08vgtQOOWefePkDCq9vh4pkQ9kPQB1sPwJ2Xv7mA/EiOHK0DkE6bdHRkKJUk0ajOyy/b7N1bQkq4+mov11zjR9cFn/8orNsO551gzvfgoEVvr8nixQaK4ooulzNDUIflU9QA4aYIHVyB5eJymliWPOabLsCAoZMr6pzn20VVaJCkHWHJjGfYvufDGIRJ0c4cruIluiggadYrePny2/DkkswlxrjyCunsDkJXbaewrx1SC8iOJmhecZxwygQej+Dqq99ee3l2op7IAvJnuPi1zusYdO5MOAIq5oEF0cO/t3EEzJH6oo8sLZ4CATXHoIQCOlm/n2LGg9Wtoosi/toE2QMTNvO6ggkkimBbEC9BIgu7usBrQmMFjKYhUYL/2gjTa2BOFVQFji2uhobhxz93vv/ERyTr1g7z0ktj6LqJokAiIdi718v115fh96u89FKBFSt86LqgthJuP4HvF8CLL+ZYt65AfX30fVMP5PLOky7Cys6zvYr3Fq7AcnE5TerqfIyNFYjFJi+4GcRA7lZJNoVQsQjZSQaStbS0HKRIimrmEyPEncxilDwPcIBOvUSBNDet/QFzd6+memcnVoNB77LpZFMRZoU+Tv3SKWrJOwHX1oBHhTLjcOpuMiQ2IwyhoFLOyc9rsZGMk6WAiVfRuKnOj2oIcjasKHtz/VVYd6JXnWmo9EK8ZJPS4oSDmwhLjcFkFfF8DKkI8h0+LDTyOR/mqAFSgSpAs0EoxA1YlYVZeRgpgEeDshAcGIJtfVARg/wIHBiATB5uWeqkDj2T6NXtuyCRhFIJ/vTP0uzYBoFAFZGI5IILspSXm2zfbrFy5QjTripnqEzhd/02i0IqdSc5cee663wsXGhMSQ2di8txcVOEU4orsFxcTpNLL63mZz/bf0yBFSjaYKnsGDsPqRoE7RTbxDz+qsGmhfPw4rSaedA4QJp9FMlTpPLnD5MbW42vp5eViWXYvQaL6IS7NCqbFiDeodqQoA43nURXUT+97GQzAsF5XEwZJ/Y1GiLNOjpJUUDgRMi2ZrxoVhM+K8gPB+HTNdA2UcuvCLi3FZ7qhU2jIBSbeS2bUT2SUKlElRilr1BPcUjBKmqYORU5rEMJ51VOAyxnBI1lQ96ArgAkC1DMQKYdigmoCjo1Y+VhGI7DDefDeA5e2wdXzj36Oma0wcrVsG+3zd6dJZBe4nGV3l4YGVW5/Mo0rbM0VhZhXVihvsXDXw6ZtO6ULPdoLJ8BGw9AtgDnt8F50ziqqLqsTKWszI1cuZxZggYsbzrxdieDmyJ0cAWWi8tpMmNGmOpqH0NDeaqqjvYpulmMsrUQwrY0tluLQLFREHx6nnqUq5FEIAFhmpQbnajzI+TbB/FRoKhKiiMlvKkCOYbQUdGYQjOnt4mc+NgrkW98fzxGSPMCe/FjUIkTGttXgKxZxFQ7MVJtlCwfD/RJPt+WICMy+PFSrsVYWq6wcRBMYP+BVpT5B/FqNjGvJKAlYTiM4k2R6K5wPo2bQIDD/j62kx60bbADMK6CUoAD4+CxoXZCuyoCfB4IeMFrwKv7YMXsw6nCZBIefxYGh2DBHOg7WKJYECSTCmNpKJWrHEh72LXSh8c2GZytEB20iM7WsBKSzdJi8HmVB54TXLkAAh745SvOki+YPoV/nNNESuhJwljO+bkyAHXvHj9cl9MgXYCV7Wd7Fe8tXIHl4nKa6LrCxz8+nR/+cB+dnWkqK734/c5Tqli00IYy3KW084KnmYRPpTms8tyNObIeEy9BtCMiUfOIUcMI/ZpN6YJmxhhgdHYF0/bsp9fbTGCxh9EagxFeZAydBm7CewrpuDNJLQ0IBAoqZSexps304kXHz+EGgcGMxtb2GGBjkEEpaqyJp1lX6mFJcx8NXvDJaqzsbNIeWB5cxWJzM0YmyavR2dQZKa6IPsnQLB8ZGWSjfSEv774KWziRH00vIU0Vy9beGLo9lgRNBY8AswiagKLt1MTHM9Ba7fxeUyGfcLoNfYYjPn76kFN/VRaDNRugZ0CQz6skDCjMM7B0AUJheFiBMR0Mi+FdGi8aQAGUqKB7E6A6VhEXznaWtW7vmwXW6Cg89zuIx+G8xXDhhUdHuKaag+Pw6F4YSh8+l5TQEIZbZkLT2R0ZeEoUCjbt7UXa2gyMt1ruu7wZiWs0OsW4AsvF5W0Qi3n4/Odns2XLGCtXDjA6WkBKMAyF5ctr+MMl5USjztOsXQyxgQ5AUE2Yy5mBMiGyyjH4EtPZTAIx/Qsk+AW7p9cwe/coi7s14k0hwuH5eKmmSIIRNtDAJFYNUkL7Xnj+UTAtWH495rQ5mIUCnlAIcbyq/GNQwGIPY+xjHBtJKxHmUo4fpyhJQaWOk8stZCgyTIYKDvs+jGRVtvWEEcLGZ9hYRi82GdoCY0hb8Gh7HYU6HV0U8Bo78DQUSKjDzDYVbtbGuTTxCHGRwJLjHFAqeCV9MYvrX2c8VcbmjiXUNPZSXd8PlqD3QBMjA44PgjQBAf4yIAfpHHQlIaZCZQjmTHRUFU2n/soz8WqZzcLBbrB90DMAIQ8YfoVSQCDLday0AEuB1MQF2jYeM4d3UQ5ZBcl4FHtAIZkGVYcXVsOiNufP5T2iziufhx/8CLIZCATh178FocCFEyV4pRI89ZQTTbvllqlxad89DD/ZCjEvtLzleOM5+M/X4ffOg9aTrB8722zcmONHPxrnC18oZ/Hi05z2/T4h6IHlLVNzLDdF6OAKLBeXt4nfr7FsWRUXXVRJOu204wcCGtpbrML3MEAYHx40hkmSJE/0iFRfDR5uoAqoQvK/ARMxW4cZJqWxx0hleiAKTkLRObaJSc4eozj4NIFNjyN391Fc1UkyNIPIvAoO/sXP2J+qwD9tIeUzZrDovvvwTrwTF9Npkj096H4/kabJBVKGAr/NbCaRHKHO8qBV1bFb9tGhx7nJrsWvhpx3/ZOkhIWCQBzh8bR50E9Yh4gvTymwjpbAFuq1XhSlxIBVQ6W/mbgZYVQtR9oqtjTYr8xA+Kuot02uKbyC5q3CUuuxVMFFgdd5ZuQqmis62D06l5r6fjKZIMKS1E/rYnw8hoXxxvQZqYDPD4WsY3B6eS1EQ05EC6Bv3Km/2jgIa/pgKAEvdEDEC2UR2DMI0ToNu2hQ7FfAVpxIgAFYoDSZWEWNkl8joiSwTI3M2jIQAsuEwThsOeDMU7x60eHHanh4YpbghNCTNmzfflhgHTwIr7zizGKsrITrrz/68R4aMtm1yxnEOHu2h+rqY7/k50rwi51QHQDfZC76PtBV+Pl2+PolzvfnOrNmebjrrghtbce2U3FxSBdg5cGzvYr3Fq7AcnGZIhRFEA4f+4U8gp8+ximhoaDg5dg2Co4Amfj95pWUrX8FXTlA4urzYFob5fJ8xoZXsTL1WwajCeq0dkYvjmBfVkfFhxVq1u8juXc1W7xR+hrKYGA9gX97km0//zmLPv5xpt9wA5t++QNyyXE022DmtTfTetVVb1rDDgb5x9KrZIxxfOVZDgxKbvvxA8wq6aRrIVGTxWi+F63upkmvIWPBgCnxqTY1moKCwDdxTTY2CgrZkqArbqCrFhXhVSyOPInAImPreMgy39jKAmMr67NL6Ai0sKs4j5psgl5RTj9hNooGZnmqMA2LIAWmxSKMjGaoDY5R5R2ltfwglNu8mL+GLAGECkIH/I6NpK2CkYe6gFPkmxOwynDETK0JVUlorYC4Cs/vceYYdo6AOhP6d4JiQXkldEWgcoFOoVRiJKdAXjgCrgS2ULGLOuaLBvZGD2qt6RR52TYUoJAS6JbgyzdD9RGRIb/f2aRUcmYKpjMwY8bh35eXQzAIhcLkA5x7ekr853/GsW3HqOv55zN85jMxmpom/7/bOQwla3JxdYigASM52D8Gc86NDPVxKSvTuPZat3jspHBThFOOK7BcXN4hltCMB40sRWZTe1yB9SZ2rkUrbyZSKCOwJ4w67UOI3S+ze9tfUqumaWwp8ODsO2nVu2nI9iP8Bv0rZuELBmm+SLJj9sXIe35D7mA76p4DxDvb2fTiTzCaAogF1Ziah7H1v6Hp8stRdWdNXaT4R3sDtugijCMI1LoUextVbCtNoCbBkJWiL/AqPubQQv2baqqeTNt8K5FjQMuiW5JLQpL/GSxDSenIVDXt4RFiQR/FkkJ7wsDvHWSZ5yWSWT8RX5xF3h0YokQRnYQdYXlwFT6Ro11tYdAbwWPm6FTCtKKwUV/AfDmAzRB6YJjKnMbiQDf7xhoYGS+nUe7jtpbHeG70ZkYHatAUg6AHmjzQa0GDx5kj2BwAJQJWzolmdWtw1QK4uh7+dRO0RBxd1DcOOR+UFsE4kFVAMSGXVBBlOp4hKOSBAk4Uq6hOtL8L8nGfc79XOm9oJbDTsHofbO88LLASCXh5pVODtWUrtLXCtDa46gjfrIoK+NrXoFiEsrKj/22eeiqN1ysoL3de5sfGLJ5+Os3990+e39s2BOGTGHUZ0B0x9m4QWFONbR/bE+3dTtADy9um5lhuitDBFVguLu8QHnSW0HLqO7YtgG2vokgwzrsG8JJpf5mRMghV2AzFKkirYQJ2Dm8uR14xHFPNGeXUvLSOW1b/E8+/aoJpYwOlYI5Evp9hzzQS8xrxlEy8DQotykGWMQuAVfSRskYZUGdgSwU/WerpofXCdtR942SLkp7quQQiOnvtLbyWGyaVmcktXoNlrOPPR2fSZfnI7A8g09AdLiAXdBJb3UbJquJl4aV6RZJyQyFeUFjStIGoOkqIJDO1neSFlxx+NEwqGSYuwrQpB5muHuRV63K8uQJFU6MvsoQQWS4we8gRICAUIuWfYDi+Ad2aRo0HimNzKQ+3w/5pRLPlfHwhlNVCbx78EsaTjjVDUxA6dWirc4RUbwEaYhAvOgXooxKGS9CpOrFFQ8JwAgo2eBUQWciYirOxgvPVAsQRnZXWRH1WGsg4t2C5oCwKz26CFQsA6dRexcdh/jyoqoJ0Gu66E8LhN/9rBI/jT5ZO2/j9h1Oxfr8gmTx2iKJgHU6LHg9VONu+n8hm4cFfQnsHzJ4FH74TTnLu+ruGdAFW7j/bq3hv4QosF5dznWU3QfNs0HSoaQZg2AgQSGXpbanlRd8V2KhYUiDEhOO5bWKZkhKgmkUUywmiVLbC0g/nOLDPw1BbHZ69vQivRnRxmM1qB9NppBI/u0jRr1Zj2DkkgowI0GM3Mks9QNYewazyYjXUsMs0eTgXIC4lebp4raOJa6IBxoSkbKyHpeFO/DVJEqkw7XE/gSaFylIMT7efaI9kfGYa3Vuk3NPJNKWdsD6GLkw0M0NBMShKA6/METYTxH0xKsQIJanhNUxkskgqHKKgLmTU20tBmiwU9+FXprPE105rJMXe0RDD2SyKGuIT02PcMF3QEnF6AQo2eFVnDE/egjIPPDIC65KOYLIlzPSDmYc+oL8ASChUQcoAe58zh9A2nRReSQPLAs0PhRSHUy6HatQmRuognJtuCdRyCNRAbdQxdQXo6ICRYWh2/tQ01ENvL+zYCfX1J/9vM3Omwauv5mhudlTT4KDFRRcdbSdyiEo/DKadov3jkTOh4txxCXlHeOU1R1w1N8HOXbD+dbjskrO9qinGTRFOOa7AcnE511EUaHizOdLonKvZt3U7e/xtBH1plJJC3PTj8ZYRKyUoFlXyr45QfaFNvkqBMhWZsphzhU2o1iJa7qEsrJIUFsXrGvGqGRQUMnaBcNrE8lskrDDFYjkFPBRLOhUDY5hdAV7QbqAuYDAuirxmttIt6ilKA9VnkfeaHBj1ckfjA/iJY9oGisekvHGYgF6CdCO9hcupKzXh8TfwGSPIjgoVfy6B5i2heiyKwoNmFwiYGYqaQUkYBEQaK2UjAiAsk0wJVMtCIlkycBCdWtS6qwgo0wDwi7sg8AsuDiQBDR8fQudwVbYQjrgCCBtwKDB0ewU0eZ1xObMDUO+Bkg4DOlCCjB+KZVAMghEHdQTqYxAxYL8E7xBkdVB8jt8WOZw0oYrz5qU7X6O1ML0FUiZUVsDACHzpdscSolTiqDnPmga53Kn921xzTYB43GbnzgJCwOzZBtddd+yQ15Ja2NB3/GNK6dRpLao+/nbvNXI5MCYy4JrmdHi+1wh6YfkUebC5KUIHV2C5uLwLmVE5j58b1zEoJWUMEjSzDA5VkOk2CSchu26AO+7oxttksL40h+DXJOqGDAE1TBlDDA7YyCaFvATPll68S2rQcgE6fvxTDnYP4m9rpO/yGymkfChAuDRGVWGYIWMOSwZexHg2z87lFzFWHqIgPeiUUKVJZdkAd5g/Qe0coVjhJxyxKFPjjNsx8kYj07wphP4M5Ys9zBZ7yOb91JT5SMQ99O+twV+ZRG0yEVJiC4GQEqHYgGQkG6HbU4OdKVLMe1DCKiI5yuKe50EUqQ5f/IZS0mggxJewSSIIoZykMaumwNK3pOFsYG4VbE1An4SwCsNeaFgAdfuh0QeNUWiphrEIbN8GA2FI2yCTOKlADxwqUdPCsGwWzIpBTgIKXHkeXDLhFN/UBIYOqRSEQo7gymRh3iRO8sfD41G4994wqZSTogyFFMRxTLSaItAWg+4k1B+jLrwnBXMrofo4qcn3IhdfCNt3QncPBANw/uKzvaKpJ52HlXvO9ireW7gCy8XlXUjYCHGD73q+8/B+dl/ZQigYBxljTl8l/Ws7uPKm79DQ5iOftJnhN7nsrjaUm76AGmgm1L2NYvpndGtjpBbMQM948Og30fLaMGZnP8G2aayuWojVHsCeCTFfL/MCOymzxknYeToGgoz1T8OzN0dF9TDVmV5qwgN4fQnmRPfj01OY5QEMf5K85UMgqdKHWSNn8rRvIRV2L7fKZ+jX/FgUobxIfSTB9xrv5YLuLXxk7OcQEWSEH6FYBMnQNx6iT29gXW4Zo9QgDYFQJPsLJr/2VRIzi4QKPVxn+6inDSkliupD5e17H3kUmBeEgxLmCNAk1NlweQg+t8CJOlVG4MX98LsgzKyFp3dARwmSYyD3AT7w1UJjNcyfK/nmzSmqgxZjAyEMRWPaEam/lArV18G+Z8GfcOrDll4O/7oWAhvgc1c49TKPr3Pc5u+8FOrKJ1+7EIJw+OT8FISAe+bDT7ZAexzKfYeL3uN5GM/D9BjcdYpC771AdTX8wZdhfNxpKPC/F1OkEncW4RTjCiwXl3cpV11ci8jpPPObMbLeBjxFCQXJ9R+8iOWXpMDSCCgqVZG7wX8ziIl3hRmzaLrqLj5KjgRF8ij40ElYazmoqiQMgwNqHUZ5lt8f+1vkAj9S08jhoc+q4ueej1NoNFj00iZu/sXj+G/KsLN2HvmQQYWWJGn4CMoM41aMghZAkmdQqaRbqaGrVMdiNjCmluERRQxZomhpJLUIZYzzXNu11Hd3sKhyBz5ZxLYlXfEKXk5cxBOxexgpViMVBdVjIksKoVSWdXsWsth8jWlb/ifrugTeRBse/zQq585l2rXXEqiqetuP9YcrodeEp7LgFdDsA3sn/G0nlBvw2Rth+TQYy8JTXWAsgfokBPqhFHBsH2KzwDsny/bYKHe151gU2cOlRiW/V3khyhGtab/qhcEQaLfDrREYyME//UKyd4OglIVVj8GMxTB/ujOM+sGX4I/udPaVUpLPOwXYinLqlu9BAz5zvtMluKoLuhLO+25DGG6aDrMrnSjf+5FAwLm9Vwl6YfnMqTmWmyJ0cAWWi8u7FEURXH11JRdfHKO31ykKqa/3EghowEec23FSOSo+yo6I8PgWL6ZvwwYS3d0UKlQ+mvgXgq0pOrRGEkTpMuvoyE2nhEFZ5yhLVr5O4QaDh+bei1QEl5mr0BWToD/nuHcWVaQiKGAwKsrJFzzkDQOPVSKveLHQCJJBxSYvPWiYlFSNlbErGKOKkq0ylC5jV2IOWwrLGBuowPYITE3FzOg0aZ3MH9xCg7cdX0eC/X+7i3SqiL98MzOvv52OgxoD397JZZ//PfxVzaAc++Vuy5YBdu0aZsmSOmbMmAgH2Vko7AcrSVAN88266dyS97IxZ9M9qvBEl0JZEKqzsK8X6ipg+Rz42Rjk4xBIwcgWGE4ClTBWsCi3kxQ6QmSVCkbGyzmgjLNtW5H/eZGXUglaKqHOC/vTcDABf7ZDsiFhktwOtqaiCsjsVNgzDCLnCKlQhVMblUhIHnjApr9fEo0K7rtPobr6aJFVLEr275dkMpLGRoWamjdvY6iwuMa5ZXI2QoDf+z5VVe8j0nlYuftsr+K9hSuwXFze5QQCGjNnvv2iGG8kwoVf+hLZ0VGuSBvMPLCJ5EgVFZlR4t4QvYEm7IBKSapM37UXTynNMy23Mv6ah5nTDmLMKGChUC7iWLZKijA5/Fio+MgiFMiJANuVuVxjv0haDWKhoggbpKRHbQIJxbzN2rHzKXZkKewx2eqbw7CvFlSJlVGxLB29Kk39ov30tVXRabZSll3HhyyTMqvE7mQD/65/lN7qpfiDOa5d/Rw/WDKMqL2folpOTgpMOUBnLs5YPoQYCfLiz3cQC+ns2DnMl/+wmVD+CfzJlaAY4K0hrRn83KrnkfElZEoG7YO12JqHgZEwQ16dphowLcHdr0rWjtpIwybYbzLe54Eqx7pBapJ4PIJiSKSukhoIsrszwMEDBo/9EC6aB5+7FW5b4riqp0Zgr2ojAnls1Q85sOJQ8koSPYJ1myHkgxUXOOm9Rx+1GRmBpiaFsTHJgw/a/OEfvjk9mM1Kvv99k/5+iRAgpcWNNyrU1wtUFerrBf39RaJRja6uEg89NI5pwoUXxgCDWAza2hTq6zmqniuRMDl4MEssptPScvKp2UTCxLYlsdhJ+sKdg4yOSlQVotEzPCjyTOJ2EU45rsBycXF5A83rJVxfzzdL+3l1p8YFv3mRX97yCfrsWuyQDjZIqaAUTZRSic4NtdivFeh8rZJF39xBhXeMg8VGmtJ9lIVGyUsvim0zW91DUdHZn29jg28hjWY3s8x9CAWKtsFqZSnjohzNKjDzT35MxVMHKJWKJCI6jXccZFvNtayP3IilqPgrE1y+9Bk0LxSlD0NmaNq+BSVTYL8V4B/+zyuEF8P8mbtJDFWyW1nE/4o+yqU7Psj30p+ls3oaYU+SC/07adNLdBTqeGXQZl4mjqCbbf3dZGMG/mCYhnyBuD3IP/Tdxcb2hRQKKtmSn7z0gAp6eZK8X+MDm4NkBgQHPQLVU8TsUyj0G46pqAUUncfNLqpoogi6xB7XKQ6CnlTIDcLrGRhd7qTgqjygCzAKgsrWHPGgjsip2FJFyTs189cugeoKyGScv93AAMQmPERjMejqkliWRFUPv+mvX2+zZQtYloquQ1WVxV/8RYnFiyWaBqqaoVBIUlGhAwbptM6rr+r84hcWQpQwTVh6ocKtt6p85B4FXXeOnc1afOc7PcTjzqio++6rZe7cE4t+KSXf/nYvpin5xjeajhov9W7gmWdsXn7ZRlHgttsULrzw3XcNMJEinDU1x3JThA6uwHJxcTmKWl2yAi+9egWBA8MkLi2jUPSgG0UUYbNjzkKWblhLuDJLyiuINKWIGEmy0ksh78NKquT8PgxRpDw9jN/I8SF1Fzfrj/GLzN08672Kl9Tl1Oc7KEodU/HQsG0jt+19EJnaz3AiR0xCTJqI734fUfEas1t/SmphDem/upQYCcataqJqHK8oUmgJkyrBvnkrmHdBNx9J/380vnKATVWXsqX5Urbri+ic2cb1Pc/w/7q/wUFjFl3BFi4qfwVLBfUSg2c2TeOq2/O8WqmRM3wk9Ch+UvTsauHVXeeRtkJkzQCmUBwVpAAJG3XIYqQPyAIhsFuBVxTnZxMYtqEaaAcroJEvCShKFAu0kIJoBl8c9BKk+nBETDlsqICuPoWy/eUs+9IexttVhr89nQZVYdF8J5U3NgaXX+j8zebNc2YTVlVJRkdh1izxJnG1aTv80Z9BX7dCQz0EffDaa5BOW8ydC9Onazz3XJFQyMLnU0Dx8MQzKumkQl2NIJMRSA1e2SEYzENtreTaa5zjj42VSCZNWlp8DA4W2b8/d1ICSwjB0qUhTFO+K8VVOi1ZudKmsVFgWfDkk5KlS+VxuzXPVdJ5WLnzbK/ivYUrsFxcXI5Co4xwtoSct4j6A3GSoQgkQVoafj3HWHM5L11xHcu6VrPp95bSFB2nhM4BMY1KbYSBRBVWmUZqW46yzDC+ViivG6ccyZ/4/4HCsEJqa5bBrRZGTCP+bJLWQIFimQcuVBh9DvI58KXBwGJaYTux1HY6R+chx2zCeha7LkZeeumkFeXGVvobq6laIPjb169iVe0V/Ov5/5vO2DSkquATKcr1UXJtN9Jy4AC9wTZ6R1tZb5ss1DfjvTFEOngJD/RewyXTXmO+ZwcxOUD72DTW7V1GUoTIFYNYBQE5FUpwyNXVel2DfsAPzAb7BQMyAsYktJugak76JQVUgvRoEBZIAZ4aUHJgVsGMEPT0wMAwqAG4uxHuboFMRqUvWIF/icWldyoowhmPs6/dMTid3uL8za69VkHTJHv3Si64AK677rBg6e6Gz3wJdm4XFEsQT0PQYzMybGNbgp/8JMl113loaQmxeLGPhqYA//xtDdO2kJogWg6GIRlOgpkpcmBXiX/7N42LL/IRCqlUVOjEYjodHY5Z16xZJ99md801k8z5eZeg62AYgkzGsdMIBo9Onb5rcLsIpxxXYLm4uByFQTn5WCvRsU6a+scJKGlUXTIUr8MbShPyZNm5fD77h2ZQMdKPVaaBkIxRTswzRj7qx9c1RqhnlISmwa4stlpJeSyOlZBYnRmQksrZCrI/TUVDgaYqONBr49MU6qoESk6SHILzr4KGq6HroMroq/spLt6B9CtU3FtL6RsXopUX2Fkzn23/+lX+z5r/y5/7v8HznjsxemwyIkSmFMa2GxgIJcmWHSA8P01pkw8qi3QlZtIa3o+C5Oorfsvu3gXkTJ3KyBCjIxW8tmk5BY+ffMGHXRAwqEJaONEpA+gV0AmUAU3AKM44nARwALA0R4wdAD6IYzzaJR1vrDJBqh5iFlRUw/iIRPosRjWbh9boIAWfuwgW1MICJjohJ967DQNkKY1uqCiKb+I+wfXXC66/3hFgXV3OtjU1kv/xP20O7BeUbCAI2QhkdQEZBZIWmSw89VSBFSt0vvGNKC+9oqAoFhUVgmRKkEhBS70klS6gFUtUVSuMDJd4+GH45CeDeL0q999fT0dHnlhMo6Hh2I7x7yU8HsFHPyp49FFJOAwf/OC7Lwr3JlyBNaW4AsvFxWVSAud9nuxj32C6Nsq0wYN0VreQstMU0j5CuTxCmIwbleTqoswPG7QqIVo2b2ass0jvvDRJX4zK8n5KBYEvn0SuyjI+XEAJg5U3yfaZlFWYNM+28QroWQPt+yzkDgs1LqmpgEAZBGM+9niq2fxAhzPTRoOSAr3/3Et9dDPR/+5HChhatIQ//tV/8FzqLsemvSQJeMa4/xPfxhsr8JuRu9mVWcSCig0TwwUN7IDJlsxSLsisJ5Gt4M6Wh0jZUbb3z+PxzbcjuxTK54wibRWZE/9/e3ceJ1dVJ/z/c+5We3V19b530tn3kEAgkLALCCoqiIwKroyOg/g4ozM+44zPqM/vccbRcdfBZUYdBhcURRAUJRAghBBCNsje6aT3vbu69rr3nt8ft5AA2SCVdNI579erXum6deveU6eX+835nvs9kBB/XkOQGF4KMIZXqT2DN5IlgTEgLaDG9RYt7NahBViLF5jFJOwGtkhGAwJ5McSv62eLmUImNXrcKhoJYrsawyn4+SbIO3DjUqgv874/jY0+LOvVF/SBAfjP/4REwpvjtHu3w7PbJIGAYCKjISJgxMHOCZimw840pgGu1Dj3XJ14XKOqEvwBgRCCXA6q417h075ex5vMHRFUV2t0db10RY5EDBYuPMsqkAIzZmh84hOT3YoTF/bD6hLVOFNzsDwqwFIU5bD0unmErvtXTP+3ec+aX/HtG2/F8ZsktRASiXQtKs0hZkezvN2ax1X9bYh1m0kHZ5P9Yz87GupIPZumfcdG0ktmY4/axHZvxUwMY4YlLRdARQWMPAV7Hof+vZAzXHTHi1mGxyHgwsSKAu6mPmZf4aejopHE+bMozIoRSI4z8uttlKeTuJrgwJON9M28HGLCmwVuCFKikm88+jfcdPOP+Wjdv7Nl71JGestpt0cZ0+LgOOTLgugRhyUVW9E1jYlkhC17zqGQ8UNG4EoQmgRbQK30CmEdBPy8NM/KxRu9SuNNah8FMcdBTLdxd/vAApF1MFvyuBJqpvcw7NaQlSY4JmMbbJ6+rwoK1awJFTjnzS/QMGuUmmgT92+dSV8CfAb8Zit8ZJX3/YnFDn/X3f33e+mqlhYYGZEMDEiEpuEzwO+X5HQBLmguSFMQr7ZprRFU1QT4m7/xRp7OPxd6egU/6IfUhMRvuoTDkvp6g/HxHLbtEovB/PlTbMXjs1gyA2u3TXYrppaTFmAJIfx4/1/zFc9zj5Tys4e8/nXg/VLKs++/PIpyhtDqZ+O/5WtcN9xPoftB7q2S9GhxCnqIsOWyyBflo8Y0WgmBNQjCJJzWscfKyR3UqGy5gh13Por78KMEAtAzlsfwwazzNdL7dCZeEOx5pkB6RCKC4CTAyIHr8yZ7J2Mgf2cTjNjs/8Rqhs+Zjb5/iPD2TlpXuiT+cRFJX5gN951H38BsaAU0WZxPIryvwwY/23oLB9qaee/cH7NvdxvnPbuFLzV8ignpx/LnqQwNERRpBrPV7Omfx1AmClkQZS6pbIhAOMVEtgzqBDyPtyRPCC+wGsA7XxpvFCsAmGC+NYe9RYcIsEgS8ifIl1tMW7ifaPM4A7saYMz0SsX3W5AHdLCTJs/8aQE6O+i9+CECZhuZgobtQlP50b9fjgP79nnL7YCXKgwGJbGIZDwr0P0CY8Jrv79MI27CdavKEVJy7TU6waCXgzRNuOntgqsu17nvPod774WeHsH06Qa1tRrNzS7LlxusWqUCrClFlWkoqZM5gpUDLpNSJoUQJvCEEOJBKeV6IcRy4Bh/KhRFOV0YFTXcWPFeLpcuB6VLTjrUC40m7ZBRlPIqeMsHoP8g7Y8+TShgIDSNcNM00t0dZLMZ/GUWqfEMA30xCiJCZiRLuNzBthw0PyT7RigUvMV0ywKgD0BdFfStrGfs3GlUPPAMDaNDLH+/RipfRnY4y0hZgs7H2kAX3mLKIYhWjFI1rRdhOWScICMHK3m69yLOb36GzSzl72q+yDe6/4q/DX4J19IoWD4KmLQOtfOwcw1prQxGBfrsLIWUhawsIAwbqVteis/B+7caiLgwrnlzrfJ4k93jEqPVprDVgACIcokVzeLEBBXThrAas/x57ekX36cVHwLkkEY+m+Ke5zJs3GxjOwbTYxpXFUevpPTm2L+SrntLuaRS3qT0pze6PL7JBb+krk6jISQYzmjUlsN5y+G9b4WArhOJwMzDLPQbiwluucXg3e/WSaclti2IRl9flXjl9BYOwOqFpTmWShF6TlqAJaWUQLL41Cw+pBBCB74E/AXw1pN1fkVRSi8uNOJC44h/OhqmQcM08muf86IAoHbJUkaCIQxD4iYGMKwBQqEAVU0m7ck8rumn8bxZ2OMhxvauIT8+TgFJyoH6oBdIjF/SiNOVIrRxkLLP1zGec/it9mbKc6PU9Haz8N3Psfn3K5CbNWa8aSdtF+0kr1vYmsXIRARd5OkfqmPj0Ar8zQn+b8OnuHrsIb4mbyPpD+E4PmKpJDuN2YwkKxC6hDzoBQcRA9fRMXwOBSTUC9iDN2plAiuA7dKbcyXxAia/AA30aQ72mIusAWdQwzcvS7QsASGXhlX76XhgJjiaF2y9OJ3JBoQkGhji+w+9mZ5gFuNJydO7Bdt+bfLZ/+3nT+sF5y2Bay599bfg2mvhu9+Fn93jMKRJ3KiOJh06sw51Otz2Vp0PfMCgshwix7n0i6YJwuGzO6g6UlA7VSTTsHbLZLdiajmpc7CKwdSzwAzgW1LKp4UQdwD3SSl7j3Y7qxDiNuA2gOYXx7sVRTkjVC9YQMdjj2GFQtQsXowRCJAdHSWwYCm1pkFF23RGDx4g1LAP13Gpm305mmlSSAp6Nm4kMzKIdDKkCyBtwNWR/WkMTRbv6rMxZYGAk2VYqyRpRZGLXXhK0tdeyd7910Ml1MW7qKrop1HvJ+jmSI1btET7uNh6kvq6Xly/BlIjNjJIyEmz2z8DJ2Pgs7IU/D6crT4C7x0h01eGSLrofhsnpkGrgD4BQeHVxFoCtOGlD/dIcAX5p3xYl2SQDjjtPsaNSiJDY/Qmq2gWPbRdvQ9nwKBz4zQoM2AEbyRLApUaa56+BjqArjSkBRMpwXB/kk8O5Zi+OEIuCYtmCcrLvSrsPp/393TOHHj3u12+e6eDXKKDKbF1EwT0CJfduzQigeMPrhQYG4dv/xe88XJYsmCyW3MSqRRhSZ3UAEtK6QBLhBAx4F4hxGrgRuCS43jvncCdAMuXL5cnsZmKopRY/bnn0r1hA8n+fkJVVVTPn08hkyHZ08Ps66+n6YILKKTTuLbN7gceYGD7doQQTLvsMhbcdBMbv/tdBp95nPG8zYFxCP6uC+0dNSQtg9o/dTN+XRNzBl+gv6wGUTaGsGzijJIYjJCcqIYml6bK/ayofJLe/Q10j9QTqp+gEPczuL2JgVQjdsGkJrID/UIfrT2dDFRXEhlN4RdJdMskXxkgnzXJro0iriygS0nZ0BiJVBzZKNAabeQwFEZ94Aik1GCOhnZxDnrB3mUhdrj4zs0jl+Vx0Uklw7zw0HLCQ+soqx6l7fy9VFYMsefpOSQPxKBQTHOaEno12FoARwe8WloF22J/RxLDzFIX1vnyl8F1dZqaNG6/3aus/uij8OhjWWxXIPwgq3QYExCFQrvG82OSr34Hzl3kzXNbugSmT5/UH5fTnq5DRRyCx78C0BknHIDVi0pzrGOlCIUQPwSuAwaklAuK2+LAz/BmUnYA75BSjgpvJOZrwBvxZjq+V0q5qfieW4HPFA/7BSnlj4rblwH/hTcj8nfAHVJKeaRznPgnPsLnlPLUxC5CiH/Cuzn6I0C2uLkZaJdSHib7/5Lly5fLjRs3nuQWKopSSumhIfY88ADDe/aAEJjBINOvuIL65ctfVYwxl0jgFAoE4nGEEOSTSfY+9BC//9rHEYkETf40W6+7Em1shOCefmJNEqc5ynBjLeXX1DN7bAd35L5OMh3hwOZZ6LECVjyLbuXx+TOIkIshHS7o28hHct+FwRSu0OmumMbaeSuplUO0BNqxpcX3Om9jNFeF7NUZ7S0nHzBxW3U018anZ6mt6kY3JbJgMLSvnHE3ii/pEEkn8E9kyU03yBhREpvCkLQg5iL8EpnVIOt9bt1nU1PTS2VVPxMyikk1DT0RnnrAINsuvZRhP5CyQbreX04BoGGQZ/oswdveYmHqLtu3C847T+cjH9G47z7BXXcBIsUfUiaySffW3LGBBIghaNVc4lLn0osEZVFIpuDGG2DZOafuZ6OvD3buhKYmaGs7dec9mu7uFA8/3M073zkdv3/yb7AXQjwrpVx+qs5XUb9cXvOh0lxn7/rc0dteHGxJAj8+JMD6V2BESvlFIcTfA+VSyr8TQrwRuB0vwFoBfE1KuaIYLG0EluON+z4LLCsGZRuAjwFP4wVYX5dSPnikc5TkQx/GybyLsAooSCnHhBAB4ErgX6SUtYfskzxWcKUoypkpWFnJ4ltvJZ9M4uTz+MrK0HT9sPv6otGXPbfCYea+7W0MDu9g1/rf4O7czKUHH2P38uV0tS1krC+NFQ+xvG2UaMdmuhoa+JTxr3zR/AcaAvupG+yhe7Qea1mWhXM20ptrYd+u+dwkfoFhJzGeHAUJzde6iL0X8+Pw+5hesZPLmh9hutbOgYM25hybSM0oE2NREv4yLFEgGhnH0S2SMkS90UXK52fCieLGJOXNI/C8jj+XIatHsOJZ8hMWjGrIAt7cLBeEW8AxTfpzNWhlBaRuUO/TuOICg1XzHb7wbg1XLy7Fg4Z37SjeGSkkhiGIxTS6eqGlXvKOd2hcd53G888Ltm2DGUvyrC1LI7vKISNhUHipx5yXbj2ga6QRPL/dW7Nw7jx4+GE4Z+mR5xi5rldXKxY78Z+LdBq+/33I5by7Hj/6UWhoOPHjnqjych+LF8exrMP/jJ4VTlGhUSnlWiFE6ys2v4WXsls/Ah4F/q64/cfFed3rhRAxIURdcd+HpZQjAEKIh4GrhRCPAlEp5fri9h8D1wMPHuUcJ8XJDNPrgB8V52FpwM+llPefxPMpinIassKvrxKL0DQufN8nseIaPVs2s29thvSvH8dvBiHgxxJZdi8KU3lzHbNTe+ic3UKjs5/1YjXdla3gk9Rk9rMwt4vN8nykgKzmwwi6OMICIdHDklzEJOcz2TKwhLGJai6b/xCOKxBJQZQkTryfhIwybFag+2xS6Qjh/ATpKhPfhVka7G6clKTa7ae5uYOdjywkMZEkFyuHLry7DYMUF32WyHEAieOa9A80YAZcQoaf3/cK5sYFF90qWfdTcKMubgAYEV51eCSaIZm+QBCvMhnxu5Q16Zx7mUE4LAgGwUWSWXGQ3Y83YFoZCoN+MCRkhDcCFgA0F3faKNaSYfKay+YDFbQF4riuzhHiX37/e1izBm691Vvz8ESkUl6Q1dzsVZsfHz89Aqxg0GDp0srJbsakCQdg9ZLSHOsuqBRCHDocdmdx2s/R1Egpe4tf9+Gt4AnQAHQesl9XcdvRtncdZvvRznFSnMy7CLcCS4+xj6qBpSjKERmWn/pCFev2S/JpiiNAaYRIEw9Dw5Y01ug4vavrCZSPUxftozDHZHbVVv5i87eoTvXztHENjm1QsAy+a/8l/6/s0+i3SiSCnkAT663z0QMugahLT28NQ24FNVWDyIERgkGD8bJKsgRoTnfQM9JMOJ+iEDLIBP1kBwK4umBB1VYqtWHK5RjL3r6e2l0N/OHZN8I8CXkB7XiV210BmunVy1oKhbQP0w+9ExoD+yHt03l+vTc3ijSwGIRmEp5w0BIuDQt1vv4ZA92E3w1JQpbgZ/vh7yq9wOfGd9v8t+sQbh8mmwgiBw3sCdOrQJ8Gy59m+sX7qLmkl/6hGlr9OkNVnYw0DvPbnS30PGVy4bkaixe/vEK8roOmg1aClWAqK2HFCtiwwZv7dTJShK4L69d7hWxnzy798aeiZBrWbirZ4YZOJL1ZnC91UucvnYpzTH6iWVEU5QhyExM88u/fIZN0MSU4ElwJARMsEwZSEOzIMTPYSbpMMnFtmAvrH+df/uc91I0nWPPuN+EIjYCeYTCks1ks4bbcnazSHidvGPzRugxZCem0Hy0pCNSkCRgZbHxEfA5tG58jf04tW+pW0N3RgpPXcYXOWLYcI1fAdQykK6h3+kiZIUYmKnCln6pFCWKMM/isBdsNb81CF686YBBvFuoLwCpBpk8gx8EahY278KbeJoA2DaIass5hwgR9TMffpmHn4I8bINMk8JuwLwGP9cI5lXDOIp3f7jIJX5DEeqrAkOXzFpmOgIgXkAVBz8F6BvdWQCW8EAriq8mzSzrc/39tcu06xpfghjcK/vZ28efJ71deCStXeosZnygh4C1vgWuu8QqanozSByMjcM893siYCrBeg8m9i7BfCFFXrDBQh1fCF6AbaDpkv8bitm5efsNcI17Kr7v49Sv3P9o5TgoVYCmKctrq27KFiZFxLAG268UojoSQD4azkM4DY5A2bM6vHkC/BD42/m9UDSQYNhuodfqQLsT9Q2TKAgxqNewLttFOG0LYROUQVwcfZFdgAXv1Ngppk/5sPZFAgmqyiP5xGnckycTrSM2MMrQ/TiIRxSfzuC5oEQcpBQ46oXSOcbuK9HCE0aEYTkcYc0RS6C8u3SP481woXKBfwFMCOQFkvZdw8NY5rMSrAL/f9XaOajhBybguuXudoNyF1hD8cQyml8EjffD0EPzVXI2rK+NsEGuZqI4gxzX6OhrAchHjkqCvC9oESaOSllgnFa17Cfak2PjfKxj/U9CbhF+A73xH8r3vw6f/RnD7R6GqqjTB1aEsq7THO1RFBbzvfd4cM+X4hIOwukQ3OrzOQqP3AbcCXyz++5tDtv+1EOKneJPcx4sB0u+B/08I8eJ3+Q3Ap6WUI0KIhBDifLxJ7rcA3zjGOU4KFWApinLaGti+nVBNLYW+g+RtB6c4oJ/News+u65XAHJwAFLJHOOZGOW93Zg+GB4LsiCzg+qJHrqtBqLlowR8adKZEDkM4oERMtkgiYly3lD2IJnQ2+hITWe4EKdCGyBaV6Civ5eGA6PkW2rYN7+BinnDTOyqJWGHYdhHpHIcw5SMZ5ZzfmI3v9g6jwM91WTG/eQdr7QCTcAoXmCl40VSCcAvoVZ4c7T24wVhPrwZqxVApnj3YEaHWRJqBD3l0BOA/3slbEjDBaNQG4C0A/uT8PwIrKz1syp9gEdntxA4kPYqzWchlO+n+cYO+lqmUWb2snjBVrS8y+OPX8z4UzFvnlZWAi5IL035/74kyGV0Pv5xQV3dqf3enwghYGGJqpKfLZIpWPvMqTmXEOJuvNGnSiFEF/BZvKDn50KIDwAHgHcUd/8d3h2Ee/ES5+8DKAZSnwdebPXnXpzwDvwVL5VpeLD44CjnOClUgKUoyulLSmoXL6Yw2ENh/wGcYgrDkd4gkCZACvAHYMK2GIjWsvm5Rqp620mNj3D3nVfy6Y9/hfv1q3gwcg1dxjQcv0BYkqQbIONEiAcGSaVitPr202M2YAibanOAaGIU35YeIhdZDHdMIOdLDuj1pIICy8nSYgUJ5xpozbs4I4I/7JhD94DETWnohvRuQi8X3u0+Gl5asBPYgBc4RYCkC2HNW9cwC4Txlt8R8qVFpIN4ayCOQd4HiXpoqAa3wzvMUAGenICxHMyYgAtqLW6pr8EwevhVRSUjNaNM9EaJhUexG+NUjAyzquEJ8v4I+3ZOo2dzHWS0YpFT1xtFKwaydlpy9902kYjGZz5z9t1dl0x6I20nc7TttHLq7iK8+QgvXX6YfSXw0SMc54fADw+zfSPwqpKwUsrhw53jZFEBlqIop62qefOY6O5m9s230P6jb9FzcAQXSOWgqgJsP5gWVNXCI0uvZb69nQeGVxPv3kjLwhQjP9rCLfZXed8//YI3JX7HluAC+sL1bEkvoC9RxzS9gwsmNrKzfC4+N4uhOdSavSztfZaKf1lHbm4VfW+oIVqvc762jl3OXAKVKdoPzqJ7OMvCgz3kfCl6wvPoTFTjc0MIV2Oiq1jt/cVRKVH8twmvas+Q9IqJ7hEwjFcQdAIvqKoBbAkxvP+vu3glHmJgxCVXT/P65rxKeG4YOiYgmYeYCSMuCDSa9Ov5X3UDnHvrAH9sGuGJRyzGskFGEhr5YIAVtVtYc+BiduyZD1kdXAiYKSKhMQbGqiEgoEJAj0t3j+CnP5PcequkqWkKrxVziHRasnmb5IGHBRVxwV+9H/z+yW7VyRUOwuoSVd1SaxF6VIClKMppq3bJEjoefRQrFGLexz6N/sPv0LOnA8d2GR6BSAU4NUH237yAtr9ME3d3Yr4hxpbN5zCUGeCSdw0zJtby34PvpHV+Lyk7xP7EdHwSVkWf5DxzAy0bDzAaKmeNuxoKBeznbO7dfxkd597OuFVFRd84Myt3UUcf0/S9pAM+grVp9jwS50ltDjcMr6c5KHnWMTC1FInuqJf6M/GCpDxQLr2RKVOC5aDNtfH5MvguySP6BJn7I+S3BpAJDakJ725DIaEML8DqgfgKhxUz4BMzvZGkpjB8ZA78oQ/+OArVflhd4fWbhoXfrUQP9vGG61JcfmkX27pcvr3NT5lvmDFRTue9rRTaTAi7hINJLq5dy6aOxfjNLNmQD6p0GHBxcxodHZIvf0Pyuc94iz1PVa4L/3lXgR/8yOHAQUE2I7ngfMEtN1n4/VM7uEymYO3Tk92KqUUFWIqinLb8ZWUsfd/72PLjH1PIZJh+8/uo7DzI8PMbMZMHCF5hYb2hHN8siRNpY6V2Ka0XXEnurvcz2L6TZO+3eNvwAL++/1kGnmqkYvEY1zbcR7AqS3l+nC6nGuHoZDMGz3cvwEjrPCRvJuob5EM/+zseXvlhtg8spi9fy+LQFtJlAfxOGq3MpbZ+gtiWHt74tioe220T0hzSrsD2SWjBS7UFgbCEacWcW9DFDOXw+3JYeg4zm8NtMjDfNUoGgTEC04XDULefzoKGGxFofkGN7nJ5rcu/LTeJFjN1zzPBk6FRatos/r1QBa5Ota/YcdkXIPHfTIusZGsgSkZPE6wwWBKrZkdyhC2JxST6y5A9BlZDlgXZbTh9Go6roSFh0IVRL00phAQpGZ+QPLcNLr7w1P8cnCoP/N7ms18oMDoImYyG0HUefQx27SpQufIsyBOeohTh2UIFWIqinNbKmptZ+bd/y+COHYx3dlK/fDlV//AZgo1+sgcfotvchV1Zh19rppHVaFgEgvU0L6gnkxzHWvclPlCzm0TucWJ/TNN3RSVjvnIKWYPKwVGoknx93R2ARjQ8ypVPfZ0LfvRT6pw098vbyZRF6NwWJupL4Fyq0yAO4CZtnKSOHYtQ4bNZ2DDKE+2V7E0FcVuEN4cpjxdkTXNpGu4k4KQZaY5iB0xAkkkFsTWdcDCL7tNZ/OEOAk+nOLijmtnNKdqilYwFfOTdME2O4LMLLWp0bxSlgMtaRggXTLan80wLZljkO+Q2P5kFmafV0bCTi/jPJzMUEhHe1hJguK1Au5hP9XkW+34RxefCsK+CmfG9RPqTDCWrvFnitgsITFMnWuYSiwmvPtck6uuz2bYtRyYjmTPHYsYME00rzchSzwD885dtRobySOmiuSbStbELPn7yPzYXTvEAKxyC1eeV5lgqRehRAZaiKKc9w++nbulS6pa+vHax2XoLs5G4FNAwEbz8Yhs47y1U7ugned9PsHQYdmxSRpJMpJqufBPTrU62WPO4dMUTmFaKuT+9h4Vr/ggZk7GqGewJLSquViMY2FVL7eoeknaQ0QEf6do4l7CD0cFp7BuPkMib3qI2BYGeANeVyJTkum33s7J9PW5QYOy0uWvVTXTUtqAZDjYW5WY3vqBDtkxy0Vs7ufotPaTTKfyh6ThuHdX9EUJ5nV9vg0tnwrJm0BHICYtfPu4jk9VIWBY1q6CmrPjB/UvBbAI9jm9Yxx2IYQggC7dPa8alEfcvBXeMCR5YB1l3HmNNMZZWa/T+3iQ7IXHREBpIv8TXqDOcg4Al+clPXCYmYP58wbJlgnD41KTOtm/PcffdExiGwDBg3boM553n561vDb9qbcvXY08H6ALsvEA3NdB0XMfFtByy2VOzZu9kSiZh7VOT3YqpRQVYiqKc0QQCnSOMLmgasfd9GO2C1Qzt/yO2fwx/yzDB0W00pjbyP/Nu4KA5DetgL9O++gsWdz5JOAvDV8/lP972RXIPWt7Ec82heeU+RpxyZt79S/xmLUuHaugPzeQe2Uw0kuHyth10rHHYWLaAHirBcCkbH2ViIsqT5RfTVLafSnuQ69fdx9dvuh0csESaCBME3DzVxhA7HB9+MUAgZHBVzz7qxQR6Qw3//McA8SDct90LsDQEZburqc7naYlruAmLNTvhnSte7BQBRhUAjRVw3XLoH4dLi/dVaWhoOnzrf8M/DUPBhvqqejQNfnZPnm98M8++XgPdktTWw6pLDA60w7f+w2XBbO+uuocflmzcKLntNo1I5OQGWfm85N57k1RX6wQCXjl515U880yWZcv8tLSYJ3yOaY0wb5HO9s0a+TQIzcFvgaFLVq08C+6glEx2odEpRwVYiqJMedE581g8Zy45UgBkC0kefOI+Wu/fQ8O6n9E2sAurP83uLj9vimbZGzCobBrgog8+TKq3jPKWMZLVYZb2bGJF13rahy5hV+hKZrVVU10zG5c8pNPEc09Sm7BZO/cKegsa9UO9xCc6GQzNJpnxMycoaZvYh563KeDH1S2QBuWiHyF0IiLITtdg8XA3yUSS4NALyEQfc2puYUcfLG+GJ0ZhZwp0W6eeABUS9riQciBfgCd2QN8ozG2EpW1erHXh3Jf6IpWBoP+lCuo1FS/vq86OAqsu0Yh0alREJMNDEr/hkhwENyKoqPDeGInAwYOSp5+WXHGFty2b9epnlboo6dCQQz4v/xxcAWiawDAEBw8WTjjASqUcOvenuPFKSVuVzi9/5dK+H0xTsnxJgXfcOPVXdQuHYfX5pTnWXf9RmuOc6VSApSjKWUEg8ONdKP1mmBtWvJtOZx27Iw556wKGoqOUJR7l4EgvFT/fxFXPfZ79119PZn4FB2JziRSSvP+ZO3l04aUcTF/Iip4BfMMFhHsOhhZBxsuJXHQBc0NhZsVgMJfhwIHNpPu7KTN8jNc30zNYh1WWppAUuJpLzhekq9CC8EsatCwB3SKd0+nqDzJm+SBmMd7fSeMcWNwEC6rhs+2QsOGyeugfgseHoUuA5Yd7NsC2vVAWhC37Qddg0bSX+qB3CL71S7j6fLho8eH7KZ8HofHnZKsQMDYCQggc9+UjVVVVsHWr5IoroLMTfvhDKBTghhtgyZLSfe/8flEsKitflg50XQiFTmyBRNuW/Nd/DdDdnUNKaGnx8cCvq7j33nF+97tRPvvZGiKREizCeJpLJmHtusluxdSiAixFUc5KZjDI9CuuoPWSS0gPDWFFo2z71y+y+9ufx69D8959rHrgOzyw7IPUjY1xc/pnJJwgj2euIzJ9HBntR4TmI4orIAtNw2puAUDXMtTXriF49QCJBZLOzVli6W4OahXc3fgXaI6LMMESNhknyGC2gUZ/N65TYN9dGvvaq8jZCRZd1sMvzWvZ1w6WBm0V8OYqeCoBW3SILYNFQ9BUADTY0gXNFWAa4Liwp/flAVYoANMboCZ+5H45/3yD++7PU8jrDI9KfBaUxwXJlDcidqhCAYJB7+vNm72q+rEYrFtX2gArHteZO9di5848jY0GmiYYGXEIBgWzZ5/Y5PNEwqa3N09rq1fo6uDBHOEw3HJLGRde6GPu3GApPsLpT6UIS04FWIqinNbG6SDBASpZQICKY7/hNdIMg3BtLQDL/s/naGzdw7Zv/Ayr1k/h8mre0XcvjQPdiCad7/vej19ksA2TRGacQGwfuPNBe8VF2DcIZopYzVIi9f34p1/Ib/oNuo0M80PbaSw/QLs+m/3uLPx+g4gsYyKfJjTcy0RPhObZcYxtPnZr9fiazsEdBsP0KtefF4N9DiTy0OvAqjqYSEJzEPaNwO5uqIxCIgMNr+iuaAjef93R++OSS7yaT39Y67C926CpWccxBNWVLk1VkmzWmxMVCsHQkOAd7/BGlGbNgvXrYXgYlpeoYOWh3v72MPffn2LLlhwAdXUGb31r+IRHsAYGJI4j6Ovz1pcsL9cJBnUMQ7BkydRPDb4oHIbVK0tzrLteVVv97KQCLEVRTls2WbpYi0AjxzgzePNJP2fVlR/jgg1PkkoNEPZ3oBdAWtCfruIJeRH1lT100ohl5xnODFMZyeMVvDqEE/Jya74EOhYbszmy9cO8s+5B2oLtpESEaf4enslJunPTyWeDFLQGrKoo0jdCYMDAik2nYmEdN7SaLBqG2jAEi1ONWn2wNestbTgvDNOKgdSi8+G3G6BnBC5fDOfOeO2fX9MEK1darFwJ2Rz0DYPfgsz1Gt/+tsP69TZDQzaVlYKPfMTH4sVegDN7Ntxxh5dibGh43d1/RIGAxo03Rrj22hC2LYlGT3zieX+/w49+lCOTiTBnToFIROOSS8owjKldVPRwkklY+8Rkt2JqUQGWoiinLQ0TiyhZRg87eiWTE+DzI8wTv4vsz+dsuADrnR8i/z93M/ynfkT5BKOXlfOnquvwZ7JM+MJUTQxhOA59ZoBKEXjVMUS+Ajl0EfiGeH5CZ7CuhyWRPbSF9+Gg0S8qidkp9LE0w6kYNhKhawRrBas/EOWK3RHmNoWYOdML3JbUvvz4F4ShwfRKVTUc8tHDAbj54uP7nHkJu3NgCZhpvTTp/VB+H7TWF59UCq65RrJzZ458Pk826xKPSwqFEHox1qmufvn7HUcyMuJQXq6XLGgJBks3HyoS0aiu1vD5fNx8cwzLOvsCqz9TKcKSUwGWoiinLQ2d6VxDjgR+Dpk4lEli3/UFstv/iBaqIfCRbyMaW0p2XnPV31M2awbmgYfIBlxS+nYS43GSvhAV4yO0Dh9koKwau3wRaL7DHkPL1SJzNewJPkPB0vD7sww4NVSb/Vhanu5kDWPZCBgFfIaDLTXy4xE+1xIi3myxfwBe6ISGOJSFXn7siQL8rhs6M2AKuKEBFpQdthlH9KsEPJcBBLw9Aucdx1SjOXN06uthYMChsRG2bHHZtClDPG5yww06lZUvD36+850+1qzp57zzKvjkJxtLVhS0VIJBwcc/7n3wUtTSOpOFw7D6otIc666flOY4ZzoVYCmKclrT8RGk6uUbdz3JaM+DyLFxmOjDXvN1ou/5culOKky02psJV19H2Oml64dfQYg63IoAw7EKxvxxynzNzNFnH/EQtpSslRm64z5yQR879Dkc1JqpcAeo0/pIO0HQIGq6VGgaK7HQ/QfZLjX2P1vHrgM+9EIQvyn44OVQV/7SsX/XBz0ZaAlC1oGfdUNjAGKvYb733jw0WTDuwP4CHKuIdzoNu/dqfPKTETo7fcRikvp6i3/8xwK/+EWB7m6Xf/5n689BlONIfvvbg9h2noceSnP77Q0Eg6dfEHO2B1YvSiZh7eOT3YqpZerfe6ooytRTyJGr0jESNlrGIVtVODnn0SJgzqL1qr9HdtURfy5I7dM+WnpbWBg4hyiRw75t1JZ8T0/xx1CWdMZEdx3GtBgpLUi/XssuZlOtD6AHbRZEerg0MEKg7JeUBf/Aro6fM6R9j4qFjxBbugF8aX6/+eXH78pAZXHgzK8DEsZeYxdcGoLeAmRycJ7/2Pvva4f/vht27dVoadH5xS+S7NuX4+KLBYsWCfx+iTyk4LmuC974xkpsW3LZZRUlTe0pJ4ks0UMB1AiWoihnolkXEJg4j1TZNmQ0TMWq207q6WKtrZx7QwWJnTkaoxCIx/9cnuGVCi78OJfhoJHD7tTx1fuIlI9iOXmyjkXeMIjbw4yYca7IrQHRggz1YQuDQGIE/1AvvqFqjGGL7mlluNM3M9K3FAcfevH/xNNCsGnMu3MwZXt3F8ZfY7WCC4MgOuHXf4DHW6H1usPPw3rRrJnw4Q/BjOnguhrZrOSb3xznn/4pzoIFFnV1Al1/+QHuuKOND3ygmVDoyJeasbECIyM21dUm4bC6JE2WcBhWry7Nse5SixECKsBSFOVMVFZF/KJ/J5xpRwvWYJqVJ/2Ui1ojPN4fIVh+5H3GHbi7J0d7OE9Ay9PWdIBAZZr8QRN3wCBQm0EGJbvL2pgdaKc5voegNsQIDoPpKrrTdbhJl5juMuEajAgYrhygrW4bDxLlYqYRwcfVNTBhw+4kBHV4dxNEX8c8/4FuwIFdB73lcqyjHMPng+XnvPhM56MfjfHNb44BsHjxS3f0SSn5058mWLAgQG2tSTh85IN2dWX5/vd7sW1JKKTz4Q/XU15euhsWlOOXTMLatZPdiqlFBViKopyRhBXAZ80/ZedriHqP8SyUHSallnPh4X6XLZslsWsyTI/vwQnoJPvDVMQH0Ka7HOxoYvDhBvIpi87ZM9gyfQlkYGh7DfkhH1Y0T3lLgupYgoVVPVhl49T7dOaFAqTJs4FOLmcGQQNubfFGywxx9JGnw9lzEHa0QzAA5y+EOdOOHlwdTlubxb/8S9Wr7ryTEnI5ieMcOVc0NOQVKN24cQJNEzQ3+9i3L80TT4xz1VVxLEulE5UznwqwFEVRjtPqFrh72+EDrO4CHNg5hDsRo7a8Gz1kE0uPopU5EBXs2DKTsbV1pISfwPIMdkhwcGgaaBqyFQqmRToRYezZclItY9giwtLKF6gJ+wjgw4dkmPTLzmkW45CeDOQcaAqCcYzYZH83/PA33nqEyTRcuATmTT/+PpBS0tVlU1NjHLasgaYJrr32yLc0btoE99wDZWWwaJFBOu0wNmbz9NMJRkcLdHRk+NCH6vH7z4IFlk8jKkVYeirAUhRFOU5zqqC5DHonoO4V89vHbHDzaXz5AFH/OJWhflIHIxARSNdhpt6Bc3EXyWSEbl8dTaEDnJvdRFBkeEheRee0FvKOgX8sx7LKp6mP9eBLQX30HASCCbJUvLKgKbBuEH7b441izYnAu1u9OVlHsq8TfKa3XE48Clv3wJuPs3YWQHe3zTe+McLb3x5hxYrXvoxMby84DoyOwoIFZQwN5Vm/fpy6OotzzgnT2Zmjry9Pa+ur64spJ4+XInQnuxlTigqwFEVRjpOpw7sWw/eefXWQFdKhojbBuGEgRsFXWaC/O0LT/E60gI0Ws6mqGMEJCVrHqjl3+xZG7HJ+lH0P9XN6eF/8e8T9YwzJOF1d9fQkGlgc6CPlbCIpLsDJh1kqmnCtlwdQjw9BXcC7m3DXBIzmoeLwpbkAqI5DJus9hsehrem19UFNjcENN0SYPfsoJzmKVau8NQxra2H79gw//GGWkRFJTY3LwYNZgkGdeFzNwzr1VKXRUlMBlqIoymsQ8cGHlsFdW6Bj1EsXxvxeRfWK5nJk3TYMIck7FpGKcaoCfSyKbae+ohck7GE6vqyD6XP4Ve56Fs/awrWVDzDH2As2WFqOZ5uW8Mjeq8ilmnm2K8bGoXlkpcZ/WXnmhfN8rM5PY8AhgEWtX2PPBAh/BuETBHU/jgsFB/yHiVMWzIBrLoLndsLc6XDdqtf2+U1TcN7xVCU9gmgUrr/eq5N11VUjdHSkMU2d3bs1/vqvY1x4YRnRqLo0nWpeirA0NcFUitCjfooVRVFeo4gPPrgM9ozA2g44MOaNKrUQZzwQIhgaIjUeJrpojIXmdprlQXzpDK5mMOirZnF+OztTc9H8kuZgB/PFLoZlOQ4mumuzXH+OZ2IX8Fj2HIb6qqj2Z0CDhKPz+LjLdruX61oGmOfz8ebGefxseIIX/P20BmGX28C9T4Wxc14g2PqKux41DS5Z7j0OtWsPpDOwcB4YJboyPLcd7n0QrrkULnjF+TTNWzRaCInPp2HbOjNmhKioeI31Jg7DdSV799qEQhoNDWou1/HwUoT2ZDdjSlEBlqIoyutg6DC3ynv0TcDeEZjIhWjNzGC9vxc3lEEzHcr9Y5jZAnlpkbV9jFsxysxxfBVZ4vYwuusQFEn6ZA1CA91wyOAjbxn0DVTj4md3ykAIjUggT0FIJgqCDeNheqsHEGYn82r9WGhMuC7/Npxka97EHrRwXhB8+lwoO0bM0t4BP7wLXBeuuwouvrA0fbSnHUbGYMceL8Dq7nb5xjcyGIbgox/188//XMntt+fIZGxuvDHKjBnHUfH0ODz7bJ6f/zyD3y+4444wlZUqyDo2lSIsNRVgKYqinKDaiPcAuIZ6nplo4ivsJiUtcvhwdB1dSBA6aIKCqVMT6mWl9gT7sm2MOuVMM9oZo4yoPcHO7GxGx6rIOmHQdPJCovuy5MpSGFKQSvkZTNksRKedDEsIUI5Fu2PT49cxZ6VJm5Kc8LNhAK5sPHr7D63A7pTwGvuGi6GuBubO8J5/7nNptmxz6E1aPLczy23vMbnpnQ2UxyTvfKe/ZOUZXNf7TFJ6XyvHFg4LVq8uTSCqUoQeFWApiqKU2LlaM58++L+5t3UZ/bKKMjNB2E1S5k4Qkkmedpaweuvv8MeG8c3O89vsNaw2n6CBXgayVWxOT8ca6CNvCmxN4gpJpGoCp6DjC+Tw2QZ+PcAc6jHQ2UeKd9OKo2fYpRXI+qG53MWXhurjuBlveiu85yZIpWHpwtL1Q6wMVq146fnYmCQQFIiM4LHnJL/b7MAAkIY770yxZk2YnT0aW9ph+Ww4b87rO+/y5RaRiEY4LKiuVqNXxyOZdFm7Nj/ZzZhSVIClKIpSatJH61AzF5Stoy9SQ0+hhlyulaxrUSt7eO6ZWp5z2lgiupC5dnL4GXNjtPum8XjdhVQVegiPjFAQLq5jYAiBdHQM00GXGgE0WmIFAniz2HPSZTd5VgsfhaDEDcBiv58I0HL45RJfRghYMPfkdgnAJz4R4HOfSxMI2qSkATuld3Ih2LZN40v/nkNrDRCPwq+fgOl1UHnkklpHpOuCefPUnYivnUoRlpIKsBRFUUotUI5uLKX80b2k546zb/pMkoEQbSP7aN19EOMrD7D36hXcs+BanPoaYnKMMbOMUbOcgjQZNaqobOij2e6no7+RfF5g95YTDCcpMwQVZS5Lwg4gcJAMSo3vuzneKTRu1sMggAgkpaTTlYQFlIvJr46+YoXB934c5S2flvD7NKCDiXclSkL7PpcZrWDbXtx1tHpeSml5KcLSBKUqRehRAZaiKEqp6Qb+ZR/CcTopbNvAOYnnCDh5hkWMdb3TsT4QQt54DqGwn21OCwNUIwRY5HAdHT8FUmUV5N0MrfEXyI3WMZEz8Jt5yoM2l1VJ6ouLTQ+RZZmIkhMWrdpL6bAu1+Un+Rx5JBK43rBYUqrbA19hYqLAunVDrFpVRTB49HMUHIhGhLfGD3hzq7MSIeD9t5rUtMH2/bB0plcIVTk1vBRhbrKbMaWoAEtRFOUk0K0w0apLmPjDb9j3bDWZaa2YA+PM2vNbJj5zJf1hEykk9aKLTtmCKfPYaGiupNIZ5nl9HqblkHcNJvQscmuQtoUDBMgg8j6eNQzSSKaLEBeLCvLS4JcD0JGFWgsSkTw+E6qFTl5K7rMLzNZ1Aq914cLjMDFhs337OEuXlh8zwDIduLARRpdYbE3kccYEhg5/+VeCq6/2RlCWzHjt6ysqpaBShKWkAixFUZSTpC8So+7aMMZvu0lt7mRDYAU/fs+vWdbYzWx3F2k9SLUxTMhN40gdv5shmw+h6w59qVr69WpMvYAWkYwFgjz3TDNLV2/jMb1AMh0jQhDTMtlgjLNtsIIRGxosGLVhzZDGm2pc0MESAildskgClD5yqa8P8IlPzEYcIypKJuE7P4BN21x6tkoWzRB85V8FT7VbJDMaG56H8nL46RMQDsCtl0D8OOaQKSfOSxG+vur8r6RShB4VYCmKopwE0nXZ+ft7ybfUUf2eGD+3/prdzlwi5Nk10MZSfRP+YBZHGFQwgC5dutONhApJxrMRcgET0y0ghcBxNLQZNpVOH7GmXnwiz2XWHgIiQ6+9hEfdC8kWypleLHNQYUK5rbEn7zDDD2NSUis0okcIrnbvLrBjh8Pll1uEw69vrtaxgiuA8QTs2gePr7OZ6LPp3+vy9htc3vNJi8oKeH4/jO2TbPyDzWO/hS/74WtfNbjqKkH49RePf12klHR02GQykqYmg0hk8uewnUxeijB97B2V46YCLEVRlJNgaNcuck+uRxY0XmiPE3yLzZzCPiJGkkf2XMp2dyHLtWcYopIxM4ZT0AkYBUYTMR5IvAn/vBQ+cuQcH0gNxjSWtmymweyi1u0jouUYcytpNjaTcBvI+GFI1ykv1CGkyTShs9yUDAmHhZrGFYaFfoQg6KGHCmzbVqClRWfJktIFEq4LO/Y4rH8izUTSJdQaoMswmKhxoMyAccHIgM1dX01yzhURrl0tSNsuD90lyec0EkLwrnfZ3P55k4+9C5pqS9a0Y3rooQxr1+bQNEk4rPHhD0coL5/KJR9UodFSUwGWoijKySAlgd1Z8ksM9IFRkjKCVoAne1czsT9Oh5jGA5vexHnnbyAcTePoGu3M5uBQM7ZjYYbDRCJjhEmSGQrjk+NEzTEyMkBW+BmRVUhhYGFjGkO0RUPsykkG3Az+9GwujgquCZrAse8Me9ObLGbP1pk1q7SXhCc2wme/ZNMYF9TUwBOPp+iqD8OICWgQBdAYGtKwsgW6eyxifrBtgWmCQJLPCUbHYDRx8gOsffsmePTREVpaoqxZ4zJtmomuCw4etNm6Nc/FFx9HUbEzVDissXp1aT6fShF6VIClKIpyElTOmcPs625k84Y7qVxQhk6e3eMLyTsmdLnsfW4mznKDbUNLSHTECFYkSUfLwAIKYOQLXOyupcbXT9W8PobyldiGIOlGecFYQIwxJBo5qjlHq2K6P0Sd7jLqT3FFBKYdZTpNvgD3PQ07O2F+C7xphcG0acd3OZBSMjhYIBYzjll53TIlyaQk2iqIRDRsKUlkAKHBQrwrUErAWo21nTZVM2HluYJAFFKjXrWJxmZ479tg3vTj7PjXqa8vz8c+tpeurgyXXGLT3i5oaalE173PrOtTe9a9lyJMTnYzppSpnVRWFEWZJELTqPrUO8m8aTVC6Mzs2ICLzvSR3fxy5M1807yduWt2kMhHwdEJOQmCqWEvU6PBBdpTlPtGKAQEecukOjxA1DeBrvlpEn4qtDLatJnM1s7HTy0jTCDMNAuydax/Bn7wCGzY+/JlcF60cS9s3APlYVi/E7a0H//nWrNmnK98pYcf/WjgmPueM1/QWifYsRNSgwX8FT6qwwKi0guu+iXsdUFCot3ghYMOMxdpvPMbOudeDxe9U/D8Np2LlpZuAerDcRzJD3/YTyKhUVERxjAE8bikq6vAgQMFqqt1liw58UWoT28vpghL8VBAjWApiqKcNAVsKi+tJHaXn1W9m9lTvYmvfuNdFIYl3/f9A3t9bVDQoBxG8hVUpEfwZ/oZ1ePUNPUy3hujdcY+Yu4omu2SDQWI6xEWijYihDHxM0KBBgIsoZGRhMZPHgpi6OAz4ZfrIZeHVfO89tiOt0h1OgumDqbhPc+8hhVShodtCgWXwcECUsqjTm43DLj5BovRYY1lCw0WDpt0Dmr85wGbvfuBvRJS0ru2Dwg2/lryD7qLaNGoWKbxf26ByCm4i9BxJOm0y+zZQV54Ic3BgzluvrmKiy6KkclIamt1fL6pPYIVDuusXh0uybFUitCjAixFUZSTpIlq9psxnnrPJQyM1HLT/XfiDuUZC7eyNncluboI5PNgguP6mWiKYAzkKUsNMT4UYnrlfhpFFyZ5gpE0hhagUlQyRogwFhkcMji0EaScIFs7wXGhPu6d32/C4zthdhPc/SwMTEBrHK6cCc/uhc5BiIdhYevxf6ZrrimnqcmitdWPEIKREZf/+I8kb3iDn2XLXj7Ko2nwtjcKXpwHtgTYuA3GVhjcvb1AVxpAeLkUKXFSgod+L3n/bRDxg5E44W/BcbEsjTe/Oc599w1TU1PGW94SZ9myyJRPCx4qmXRYu3Z8spsxpagAS1EU5SSpJMZFofcQb/8CnUPPYvUMeBOLJBz0T4MaqFo4SHrITypeTiYdhKiFWenw5MDFzGvahaY74NdI6REaNbiQ+TyDTQdpKtG5mkqaOXwNA4mXIrxrozdK1RKHrnF4vAPueAuMJr06U75D5sFv2lTgySdtli0zWLny1RPkw2Gd889/qcS6EKDrx18YVAgo5CVCCgwT7AIgQGgC6UAhA0PDUFUBdVXH3dUn7LzzIixfHkY7a9fnUXcRlpoKsBRFUU6iamMa1W1fZkLczz3+PGnf3xFNd2HU5qBaI9aYoHH+fp7fuIT8YBAKPgrDgnHN5Kk5y6mIDiO0Muo0QQ1zuJc8OSQuPmYQYiYvpXXmN8Gjz0P/GFgmjCThjUvhD/uhpbzYnjAcGAG/BXXxl7c1nZb86lcFYjHB/fcXmDNHJx4/+lTd8nKNT33q+Ne0WTwHhlbDhkcEiRHJeDHAkq4EKQhG4FO3wcxWiJYmY3Xczt7gClSAVXoqwFIURTnZ9BiRme9GTHdY638X7P46tU4PY7lmEuMxylpGqLpsiEAhQ27cIpvyUxYeQ9Zb9OdnUaUlCOl+hsX5OEgaMLGRPEWKcwmhFwuIVkbhL6+Ex3dAOg9XLIJzpsH2YehNQFXI+3dB3eGbaZoQjQqGhlzCYYHfX/qAwzDgqosFxmcEd/wvyGYkubw3D0sPwifv0Fm2oOSnVY7Bm4NVVpJjqTlYHhVgKYqinCKLFgme2mKwqXAzvn3boA2Gn66iobUdI+qQMYPISkFNQz+6bWPp0JG6lL1unmbdotlXwQEyALhIdMSrarPXlsONK1++7V3L4ZdboGsM5tXCmxcevn2mKfjgB310dLg0NmoEgydvROeyywQ/+B587wewdbugvknw0Q8Lrrz0pJ1SOQpvDtbIZDdjSlEBlqIoyimyeLFgyQuSB39TxbhYhNk7TCFZwVZjBXOv30SgNoNJAS3vYNtBQrkqCqZNmXSoTTey1BdkNzl6KABwNVG041hbMBaED1xwfG2Mx7VjpgVLQQjBihWCFStO+qmU4yIBd7IbMaWoAEtRFOUU0XXBbX+h015b4CtPVOCGTOgGe4PFtm0rqLy4l9oVPWi6xO83EFGbKsciNthGTX2ECPAe4gzjEEQQU3/ClRIJhw1Wry4vybFUitCjfjsVRVFOIV2Df1zlZ2uyl3U7AySjPkDAmMnQw/UMb60h2JjmpitcZjomwVyI4YJgenHCtw+NelUjWimxZNJm7dqhyW7GlKICLEVRlFMs6oO/WVpHyE2yYafDQMqiEBQQBS2l8/bqKAtNQWICEg7c2AKhYy8pqCgnQN1FWGoqwFIURZkEVzRDzBfmkSbYPwgTaVhZDStnwgtpGM7B/BisqITG0GS3VpnqvBRhRUmOpVKEHhVgKYqiTAJNwHm1sLwG8g5YurcN4JzJbZpyFvJShMdeX1I5firAUhRFmUSaAL/6S6xMOpUiLDX1a60oiqIoZzkvRViatYlUitCjAixFURRFOcslkwXWru2b7GZMKSrAUhRFURQFlSIsLRVgKYqiKMpZLhw2Wb26tiTHUilCjwqwFEVRFOUsl0zmWbu2e7KbMaWoAEtRFEVRFFSKsLRUgKUoiqIoZzkvRVhfkmOpFKFHBViKoiiKcpbzUoSdk92MKUUFWIqiKIpy1lOFRktNBViKoiiKcpYLhy1Wr24sybFUitCjAixFURRFOct5KcKDk92MKUUFWIqiKIpylvNGsJpKciw1guURUsrJbsMxCSEGgQOT3Q6gEhia7Eac4VQfnjjVhydO9eGJU314Yo7Vfy1SytIsDngchBAP4bWpFIaklFeX6FhnrDMiwDpdCCE2SimXT3Y7zmSqD0+c6sMTp/rwxKk+PDGq/6Y+bbIboCiKoiiKMtWoAEtRFEVRFKXEVID12tw52Q2YAlQfnjjVhydO9eGJU314YlT/TXFqDpaiKIqiKEqJqREsRVEURVGUElMBlqIoiqIoSompAOsIhBA3CiGeF0K4Qojlh2y/UgjxrBBiW/Hfyw7z3vuEENtPbYtPL6+1/4QQQSHEA0KIncX3fXHyWn96eD0/g0KIZcXte4UQXxdCiMlp/enhKH1YIYRYI4RICiG++Yr33Fzsw61CiIeEEKWqDXRGep19aAkh7hRC7C7+Tr/91Lf89PF6+vCQfc7668mZSgVYR7YdeBuw9hXbh4A3SSkXArcCPzn0RSHE24DkKWnh6e319N+/SSnnAEuBC4UQ15ySlp6+Xk8ffgf4EDCz+Djbi/0dqQ+zwD8Cf3voRiGEAXwNuFRKuQjYCvz1KWjn6ew19WHRPwADUspZwDzgsZPawtPf6+lDdT05w6mlco5ASrkD4JUDAFLK5w55+jwQEEL4pJQ5IUQY+ARwG/DzU9XW09Hr6L80sKa4T14IsQkozcqjZ6jX2odAHIhKKdcX3/dj4HrgwVPR3tPRUfowBTwhhJjxireI4iMkhBgGosDeU9DU09br6EOA9wNzivu5nOUV319PH6rryZlPjWCdmLcDm6SUueLzzwNfBtKT16Qzyiv7DwAhRAx4E/CnyWjUGebQPmwAug55rau4TTlOUsoC8BFgG9CDN/ryg0lt1Bmm+PsL8HkhxCYhxC+EEDWT2aYzlLqenOHO6hEsIcQfgdrDvPQPUsrfHOO984F/Ad5QfL4EaJNS/i8hRGuJm3paKmX/HbLdAO4Gvi6lbC9VW09XJ6MPzzYn0oeHOZaJF2AtBdqBbwCfBr5wou08nZWyD/GuK43AOinlJ4QQnwD+DXjPCTbztFbin8MlnGXXk6norA6wpJRXvJ73CSEagXuBW6SU+4qbLwCWCyE68Pq1WgjxqJTyklK09XRU4v570Z3AHinlV0+weWeEEvdhNy9PqzYWt01pr7cPj2BJ8Zj7AIQQPwf+voTHPy2VuA+H8UZdflV8/gvgAyU8/mmpxH141l1PpiKVInyNisPfDwB/L6V88sXtUsrvSCnrpZStwEXAbvXL8GpH6r/ia18AyoCPn/qWnTmO8jPYCySEEOcX7x68BXitow9nu25gnhCiqvj8SmDHJLbnjCO96tW/BS4pbroceGHSGnQGUteTKUJKqR6HeQBvxZvDkgP6gd8Xt38GSAGbD3lUv+K9rcD2yf4MZ1L/4Y22SLyL2YvbPzjZn+NM6sPia8vx7ljaB3yT4moNZ+vjSH1YfK0DGMG7S6sLmFfc/uHiz+FWvEChYrI/xxnYhy14d8xtxZtL2TzZn+NM68NDXj/rrydn6kMtlaMoiqIoilJiKkWoKIqiKIpSYirAUhRFURRFKTEVYCmKoiiKopSYCrAURVEURVFKTAVYiqIoiqIoJaYCLEU5wwkhSr4YrBDizUKIvy9+fb0QYt7rOMajQojlpW6boijKmUAFWIqivIqU8j4p5ReLT6/HW5NPURRFOU4qwFKUKUJ4viSE2C6E2CaEuKm4/ZLiaNI9QoidQoi7ipXeEUK8sbjtWSHE14UQ9xe3v1cI8U0hxErgzcCXhBCbhRBth45MCSEqi8t5IIQICCF+KoTYIYS4Fwgc0rY3CCGeOmTx3/Cp7R1FUZRT66xei1BRppi34a2ltxioBJ4RQqwtvrYUmA/0AE8CFwohNgL/AayWUu4XQtz9ygNKKdcJIe4D7pdS3gNQjM0O5yNAWko5VwixCNhU3L8Sr/r8FVLKlBDi74BPAJ8rwWdWFEU5LakAS1GmjouAu6WUDtAvhHgMOBdIABuklF0AQojNeMtvJIF2KeX+4vvvBm47gfOvBr4OIKXcKoTYWtx+Pl6K8clicGYBT53AeRRFUU57KsBSlLND7pCvHU7sd9/mpekF/uPYXwAPSylvPoFzKoqinFHUHCxFmToeB24SQuhCiCq8EaUNR9l/FzBdCNFafH7TEfabACKHPO8AlhW/vuGQ7WuBvwAQQiwAFhW3r8dLSc4ovhYSQsw6ng+kKIpyplIBlqJMHfcCW4EtwCPAp6SUfUfaWUqZAf4KeEgI8SxeIDV+mF1/CnxSCPGcEKIN+DfgI0KI5/Dmer3oO0BYCLEDb37Vs8XzDALvBe4upg2fAuacyAdVFEU53Qkp5WS3QVGUSSKECEspk8W7Cr8F7JFS/vtkt0tRFOVMp0awFOXs9qHipPfngTK8uwoVRVGUE6RGsBRFURRFUUpMjWApiqIoiqKUmAqwFEVRFEVRSkwFWIqiKIqiKCWmAixFURRFUZQSUwGWoiiKoihKif3/kHyLNMS2ZzgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "housing.plot(kind='scatter',x='longitude',y='latitude',alpha=0.4,\n",
    "            s=housing['population']/100,label='population',figsize=(10,7),\n",
    "            c='median_house_value',cmap=plt.get_cmap('jet'),colorbar=True,\n",
    "            sharex=False)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-97-f1204aebaef9>:18: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
      "  cbar.ax.set_yticklabels([\"$%sk\"%(round(v/1000)) for v in tick_values], fontsize=14)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.image as mpimg\n",
    "california_img = mpimg.imread('./california.png')\n",
    "\n",
    "housing.plot(kind=\"scatter\", x=\"longitude\", y=\"latitude\", alpha=0.4,\n",
    "    s=housing[\"population\"]/100, label=\"population\", figsize=(10,7),\n",
    "    c=\"median_house_value\", cmap=plt.get_cmap(\"jet\"), colorbar=False,\n",
    "    sharex=False)\n",
    "\n",
    "plt.imshow(california_img, extent=[-124.55, -113.80, 32.45, 42.05], alpha=0.5,\n",
    "           cmap=plt.get_cmap(\"jet\"))\n",
    "plt.ylabel(\"Latitude\", fontsize=14)\n",
    "plt.xlabel(\"Longitude\", fontsize=14)\n",
    "\n",
    "\n",
    "prices = housing[\"median_house_value\"]\n",
    "tick_values = np.linspace(prices.min(), prices.max(), 11)\n",
    "cbar = plt.colorbar()\n",
    "cbar.ax.set_yticklabels([\"$%sk\"%(round(v/1000)) for v in tick_values], fontsize=14)\n",
    "cbar.set_label('Median House Value', fontsize=16)\n",
    "\n",
    "plt.legend(fontsize=16)\n",
    "# save_fig(\"california_housing_prices_plot\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>median_house_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>longitude</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.924664</td>\n",
       "      <td>-0.108197</td>\n",
       "      <td>0.044568</td>\n",
       "      <td>0.069608</td>\n",
       "      <td>0.099773</td>\n",
       "      <td>0.055310</td>\n",
       "      <td>-0.015176</td>\n",
       "      <td>-0.045967</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>latitude</th>\n",
       "      <td>-0.924664</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.011173</td>\n",
       "      <td>-0.036100</td>\n",
       "      <td>-0.066983</td>\n",
       "      <td>-0.108785</td>\n",
       "      <td>-0.071035</td>\n",
       "      <td>-0.079809</td>\n",
       "      <td>-0.144160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>housing_median_age</th>\n",
       "      <td>-0.108197</td>\n",
       "      <td>0.011173</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.361262</td>\n",
       "      <td>-0.320451</td>\n",
       "      <td>-0.296244</td>\n",
       "      <td>-0.302916</td>\n",
       "      <td>-0.119034</td>\n",
       "      <td>0.105623</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>total_rooms</th>\n",
       "      <td>0.044568</td>\n",
       "      <td>-0.036100</td>\n",
       "      <td>-0.361262</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.930380</td>\n",
       "      <td>0.857126</td>\n",
       "      <td>0.918484</td>\n",
       "      <td>0.198050</td>\n",
       "      <td>0.134153</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>total_bedrooms</th>\n",
       "      <td>0.069608</td>\n",
       "      <td>-0.066983</td>\n",
       "      <td>-0.320451</td>\n",
       "      <td>0.930380</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.877747</td>\n",
       "      <td>0.979728</td>\n",
       "      <td>-0.007723</td>\n",
       "      <td>0.049686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>population</th>\n",
       "      <td>0.099773</td>\n",
       "      <td>-0.108785</td>\n",
       "      <td>-0.296244</td>\n",
       "      <td>0.857126</td>\n",
       "      <td>0.877747</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.907222</td>\n",
       "      <td>0.004834</td>\n",
       "      <td>-0.024650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>households</th>\n",
       "      <td>0.055310</td>\n",
       "      <td>-0.071035</td>\n",
       "      <td>-0.302916</td>\n",
       "      <td>0.918484</td>\n",
       "      <td>0.979728</td>\n",
       "      <td>0.907222</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.013033</td>\n",
       "      <td>0.065843</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>median_income</th>\n",
       "      <td>-0.015176</td>\n",
       "      <td>-0.079809</td>\n",
       "      <td>-0.119034</td>\n",
       "      <td>0.198050</td>\n",
       "      <td>-0.007723</td>\n",
       "      <td>0.004834</td>\n",
       "      <td>0.013033</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.688075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>median_house_value</th>\n",
       "      <td>-0.045967</td>\n",
       "      <td>-0.144160</td>\n",
       "      <td>0.105623</td>\n",
       "      <td>0.134153</td>\n",
       "      <td>0.049686</td>\n",
       "      <td>-0.024650</td>\n",
       "      <td>0.065843</td>\n",
       "      <td>0.688075</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    longitude  latitude  housing_median_age  total_rooms  \\\n",
       "longitude            1.000000 -0.924664           -0.108197     0.044568   \n",
       "latitude            -0.924664  1.000000            0.011173    -0.036100   \n",
       "housing_median_age  -0.108197  0.011173            1.000000    -0.361262   \n",
       "total_rooms          0.044568 -0.036100           -0.361262     1.000000   \n",
       "total_bedrooms       0.069608 -0.066983           -0.320451     0.930380   \n",
       "population           0.099773 -0.108785           -0.296244     0.857126   \n",
       "households           0.055310 -0.071035           -0.302916     0.918484   \n",
       "median_income       -0.015176 -0.079809           -0.119034     0.198050   \n",
       "median_house_value  -0.045967 -0.144160            0.105623     0.134153   \n",
       "\n",
       "                    total_bedrooms  population  households  median_income  \\\n",
       "longitude                 0.069608    0.099773    0.055310      -0.015176   \n",
       "latitude                 -0.066983   -0.108785   -0.071035      -0.079809   \n",
       "housing_median_age       -0.320451   -0.296244   -0.302916      -0.119034   \n",
       "total_rooms               0.930380    0.857126    0.918484       0.198050   \n",
       "total_bedrooms            1.000000    0.877747    0.979728      -0.007723   \n",
       "population                0.877747    1.000000    0.907222       0.004834   \n",
       "households                0.979728    0.907222    1.000000       0.013033   \n",
       "median_income            -0.007723    0.004834    0.013033       1.000000   \n",
       "median_house_value        0.049686   -0.024650    0.065843       0.688075   \n",
       "\n",
       "                    median_house_value  \n",
       "longitude                    -0.045967  \n",
       "latitude                     -0.144160  \n",
       "housing_median_age            0.105623  \n",
       "total_rooms                   0.134153  \n",
       "total_bedrooms                0.049686  \n",
       "population                   -0.024650  \n",
       "households                    0.065843  \n",
       "median_income                 0.688075  \n",
       "median_house_value            1.000000  "
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corr_matrix =  housing.corr()\n",
    "corr_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "median_house_value    1.000000\n",
       "median_income         0.688075\n",
       "total_rooms           0.134153\n",
       "housing_median_age    0.105623\n",
       "households            0.065843\n",
       "total_bedrooms        0.049686\n",
       "population           -0.024650\n",
       "longitude            -0.045967\n",
       "latitude             -0.144160\n",
       "Name: median_house_value, dtype: float64"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corr_matrix['median_house_value'].sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from pandas.plotting import scatter_matrix\n",
    "\n",
    "attributes = ['median_house_value', 'median_income', 'total_rooms', 'housing_median_age']\n",
    "scatter_matrix(housing[attributes], figsize = (12, 8) )\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0, 16.0, 0.0, 550000.0)"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "housing.plot(kind = 'scatter', x='median_income', y = 'median_house_value', alpha = 0.1)\n",
    "plt.axis([0, 16, 0, 550000])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [],
   "source": [
    "housing['rooms_per_household'] = housing['total_rooms']/housing['households']\n",
    "housing['bedrooms_per_room'] = housing['total_bedrooms']/housing['total_rooms']\n",
    "housing['population_per_household'] = housing['population']/housing['households']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>median_house_value</th>\n",
       "      <th>rooms_per_household</th>\n",
       "      <th>bedrooms_per_room</th>\n",
       "      <th>population_per_household</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>longitude</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.924664</td>\n",
       "      <td>-0.108197</td>\n",
       "      <td>0.044568</td>\n",
       "      <td>0.069608</td>\n",
       "      <td>0.099773</td>\n",
       "      <td>0.055310</td>\n",
       "      <td>-0.015176</td>\n",
       "      <td>-0.045967</td>\n",
       "      <td>-0.027540</td>\n",
       "      <td>0.092657</td>\n",
       "      <td>0.002476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>latitude</th>\n",
       "      <td>-0.924664</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.011173</td>\n",
       "      <td>-0.036100</td>\n",
       "      <td>-0.066983</td>\n",
       "      <td>-0.108785</td>\n",
       "      <td>-0.071035</td>\n",
       "      <td>-0.079809</td>\n",
       "      <td>-0.144160</td>\n",
       "      <td>0.106389</td>\n",
       "      <td>-0.113815</td>\n",
       "      <td>0.002366</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>housing_median_age</th>\n",
       "      <td>-0.108197</td>\n",
       "      <td>0.011173</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.361262</td>\n",
       "      <td>-0.320451</td>\n",
       "      <td>-0.296244</td>\n",
       "      <td>-0.302916</td>\n",
       "      <td>-0.119034</td>\n",
       "      <td>0.105623</td>\n",
       "      <td>-0.153277</td>\n",
       "      <td>0.136089</td>\n",
       "      <td>0.013191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>total_rooms</th>\n",
       "      <td>0.044568</td>\n",
       "      <td>-0.036100</td>\n",
       "      <td>-0.361262</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.930380</td>\n",
       "      <td>0.857126</td>\n",
       "      <td>0.918484</td>\n",
       "      <td>0.198050</td>\n",
       "      <td>0.134153</td>\n",
       "      <td>0.133798</td>\n",
       "      <td>-0.187900</td>\n",
       "      <td>-0.024581</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>total_bedrooms</th>\n",
       "      <td>0.069608</td>\n",
       "      <td>-0.066983</td>\n",
       "      <td>-0.320451</td>\n",
       "      <td>0.930380</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.877747</td>\n",
       "      <td>0.979728</td>\n",
       "      <td>-0.007723</td>\n",
       "      <td>0.049686</td>\n",
       "      <td>0.001538</td>\n",
       "      <td>0.084238</td>\n",
       "      <td>-0.028355</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>population</th>\n",
       "      <td>0.099773</td>\n",
       "      <td>-0.108785</td>\n",
       "      <td>-0.296244</td>\n",
       "      <td>0.857126</td>\n",
       "      <td>0.877747</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.907222</td>\n",
       "      <td>0.004834</td>\n",
       "      <td>-0.024650</td>\n",
       "      <td>-0.072213</td>\n",
       "      <td>0.035319</td>\n",
       "      <td>0.069863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>households</th>\n",
       "      <td>0.055310</td>\n",
       "      <td>-0.071035</td>\n",
       "      <td>-0.302916</td>\n",
       "      <td>0.918484</td>\n",
       "      <td>0.979728</td>\n",
       "      <td>0.907222</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.013033</td>\n",
       "      <td>0.065843</td>\n",
       "      <td>-0.080598</td>\n",
       "      <td>0.065087</td>\n",
       "      <td>-0.027309</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>median_income</th>\n",
       "      <td>-0.015176</td>\n",
       "      <td>-0.079809</td>\n",
       "      <td>-0.119034</td>\n",
       "      <td>0.198050</td>\n",
       "      <td>-0.007723</td>\n",
       "      <td>0.004834</td>\n",
       "      <td>0.013033</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.688075</td>\n",
       "      <td>0.326895</td>\n",
       "      <td>-0.615661</td>\n",
       "      <td>0.018766</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>median_house_value</th>\n",
       "      <td>-0.045967</td>\n",
       "      <td>-0.144160</td>\n",
       "      <td>0.105623</td>\n",
       "      <td>0.134153</td>\n",
       "      <td>0.049686</td>\n",
       "      <td>-0.024650</td>\n",
       "      <td>0.065843</td>\n",
       "      <td>0.688075</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.151948</td>\n",
       "      <td>-0.255880</td>\n",
       "      <td>-0.023737</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rooms_per_household</th>\n",
       "      <td>-0.027540</td>\n",
       "      <td>0.106389</td>\n",
       "      <td>-0.153277</td>\n",
       "      <td>0.133798</td>\n",
       "      <td>0.001538</td>\n",
       "      <td>-0.072213</td>\n",
       "      <td>-0.080598</td>\n",
       "      <td>0.326895</td>\n",
       "      <td>0.151948</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.416952</td>\n",
       "      <td>-0.004852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bedrooms_per_room</th>\n",
       "      <td>0.092657</td>\n",
       "      <td>-0.113815</td>\n",
       "      <td>0.136089</td>\n",
       "      <td>-0.187900</td>\n",
       "      <td>0.084238</td>\n",
       "      <td>0.035319</td>\n",
       "      <td>0.065087</td>\n",
       "      <td>-0.615661</td>\n",
       "      <td>-0.255880</td>\n",
       "      <td>-0.416952</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.002938</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>population_per_household</th>\n",
       "      <td>0.002476</td>\n",
       "      <td>0.002366</td>\n",
       "      <td>0.013191</td>\n",
       "      <td>-0.024581</td>\n",
       "      <td>-0.028355</td>\n",
       "      <td>0.069863</td>\n",
       "      <td>-0.027309</td>\n",
       "      <td>0.018766</td>\n",
       "      <td>-0.023737</td>\n",
       "      <td>-0.004852</td>\n",
       "      <td>0.002938</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          longitude  latitude  housing_median_age  \\\n",
       "longitude                  1.000000 -0.924664           -0.108197   \n",
       "latitude                  -0.924664  1.000000            0.011173   \n",
       "housing_median_age        -0.108197  0.011173            1.000000   \n",
       "total_rooms                0.044568 -0.036100           -0.361262   \n",
       "total_bedrooms             0.069608 -0.066983           -0.320451   \n",
       "population                 0.099773 -0.108785           -0.296244   \n",
       "households                 0.055310 -0.071035           -0.302916   \n",
       "median_income             -0.015176 -0.079809           -0.119034   \n",
       "median_house_value        -0.045967 -0.144160            0.105623   \n",
       "rooms_per_household       -0.027540  0.106389           -0.153277   \n",
       "bedrooms_per_room          0.092657 -0.113815            0.136089   \n",
       "population_per_household   0.002476  0.002366            0.013191   \n",
       "\n",
       "                          total_rooms  total_bedrooms  population  households  \\\n",
       "longitude                    0.044568        0.069608    0.099773    0.055310   \n",
       "latitude                    -0.036100       -0.066983   -0.108785   -0.071035   \n",
       "housing_median_age          -0.361262       -0.320451   -0.296244   -0.302916   \n",
       "total_rooms                  1.000000        0.930380    0.857126    0.918484   \n",
       "total_bedrooms               0.930380        1.000000    0.877747    0.979728   \n",
       "population                   0.857126        0.877747    1.000000    0.907222   \n",
       "households                   0.918484        0.979728    0.907222    1.000000   \n",
       "median_income                0.198050       -0.007723    0.004834    0.013033   \n",
       "median_house_value           0.134153        0.049686   -0.024650    0.065843   \n",
       "rooms_per_household          0.133798        0.001538   -0.072213   -0.080598   \n",
       "bedrooms_per_room           -0.187900        0.084238    0.035319    0.065087   \n",
       "population_per_household    -0.024581       -0.028355    0.069863   -0.027309   \n",
       "\n",
       "                          median_income  median_house_value  \\\n",
       "longitude                     -0.015176           -0.045967   \n",
       "latitude                      -0.079809           -0.144160   \n",
       "housing_median_age            -0.119034            0.105623   \n",
       "total_rooms                    0.198050            0.134153   \n",
       "total_bedrooms                -0.007723            0.049686   \n",
       "population                     0.004834           -0.024650   \n",
       "households                     0.013033            0.065843   \n",
       "median_income                  1.000000            0.688075   \n",
       "median_house_value             0.688075            1.000000   \n",
       "rooms_per_household            0.326895            0.151948   \n",
       "bedrooms_per_room             -0.615661           -0.255880   \n",
       "population_per_household       0.018766           -0.023737   \n",
       "\n",
       "                          rooms_per_household  bedrooms_per_room  \\\n",
       "longitude                           -0.027540           0.092657   \n",
       "latitude                             0.106389          -0.113815   \n",
       "housing_median_age                  -0.153277           0.136089   \n",
       "total_rooms                          0.133798          -0.187900   \n",
       "total_bedrooms                       0.001538           0.084238   \n",
       "population                          -0.072213           0.035319   \n",
       "households                          -0.080598           0.065087   \n",
       "median_income                        0.326895          -0.615661   \n",
       "median_house_value                   0.151948          -0.255880   \n",
       "rooms_per_household                  1.000000          -0.416952   \n",
       "bedrooms_per_room                   -0.416952           1.000000   \n",
       "population_per_household            -0.004852           0.002938   \n",
       "\n",
       "                          population_per_household  \n",
       "longitude                                 0.002476  \n",
       "latitude                                  0.002366  \n",
       "housing_median_age                        0.013191  \n",
       "total_rooms                              -0.024581  \n",
       "total_bedrooms                           -0.028355  \n",
       "population                                0.069863  \n",
       "households                               -0.027309  \n",
       "median_income                             0.018766  \n",
       "median_house_value                       -0.023737  \n",
       "rooms_per_household                      -0.004852  \n",
       "bedrooms_per_room                         0.002938  \n",
       "population_per_household                  1.000000  "
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corr_matrix=housing.corr()\n",
    "corr_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "median_house_value          1.000000\n",
       "median_income               0.688075\n",
       "rooms_per_household         0.151948\n",
       "total_rooms                 0.134153\n",
       "housing_median_age          0.105623\n",
       "households                  0.065843\n",
       "total_bedrooms              0.049686\n",
       "population_per_household   -0.023737\n",
       "population                 -0.024650\n",
       "longitude                  -0.045967\n",
       "latitude                   -0.144160\n",
       "bedrooms_per_room          -0.255880\n",
       "Name: median_house_value, dtype: float64"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corr_matrix['median_house_value'].sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
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       "      <th>median_house_value</th>\n",
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       "      <th>housing_cat</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>17606</th>\n",
       "      <td>-121.89</td>\n",
       "      <td>37.29</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1568.0</td>\n",
       "      <td>351.0</td>\n",
       "      <td>710.0</td>\n",
       "      <td>339.0</td>\n",
       "      <td>2.7042</td>\n",
       "      <td>286600.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18632</th>\n",
       "      <td>-121.93</td>\n",
       "      <td>37.05</td>\n",
       "      <td>14.0</td>\n",
       "      <td>679.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>306.0</td>\n",
       "      <td>113.0</td>\n",
       "      <td>6.4214</td>\n",
       "      <td>340600.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14650</th>\n",
       "      <td>-117.20</td>\n",
       "      <td>32.77</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1952.0</td>\n",
       "      <td>471.0</td>\n",
       "      <td>936.0</td>\n",
       "      <td>462.0</td>\n",
       "      <td>2.8621</td>\n",
       "      <td>196900.0</td>\n",
       "      <td>NEAR OCEAN</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3230</th>\n",
       "      <td>-119.61</td>\n",
       "      <td>36.31</td>\n",
       "      <td>25.0</td>\n",
       "      <td>1847.0</td>\n",
       "      <td>371.0</td>\n",
       "      <td>1460.0</td>\n",
       "      <td>353.0</td>\n",
       "      <td>1.8839</td>\n",
       "      <td>46300.0</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3555</th>\n",
       "      <td>-118.59</td>\n",
       "      <td>34.23</td>\n",
       "      <td>17.0</td>\n",
       "      <td>6592.0</td>\n",
       "      <td>1525.0</td>\n",
       "      <td>4459.0</td>\n",
       "      <td>1463.0</td>\n",
       "      <td>3.0347</td>\n",
       "      <td>254500.0</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
       "17606    -121.89     37.29                38.0       1568.0           351.0   \n",
       "18632    -121.93     37.05                14.0        679.0           108.0   \n",
       "14650    -117.20     32.77                31.0       1952.0           471.0   \n",
       "3230     -119.61     36.31                25.0       1847.0           371.0   \n",
       "3555     -118.59     34.23                17.0       6592.0          1525.0   \n",
       "\n",
       "       population  households  median_income  median_house_value  \\\n",
       "17606       710.0       339.0         2.7042            286600.0   \n",
       "18632       306.0       113.0         6.4214            340600.0   \n",
       "14650       936.0       462.0         2.8621            196900.0   \n",
       "3230       1460.0       353.0         1.8839             46300.0   \n",
       "3555       4459.0      1463.0         3.0347            254500.0   \n",
       "\n",
       "      ocean_proximity income_cat housing_cat  \n",
       "17606       <1H OCEAN          2           2  \n",
       "18632       <1H OCEAN          5           5  \n",
       "14650      NEAR OCEAN          2           2  \n",
       "3230           INLAND          2           2  \n",
       "3555        <1H OCEAN          3           3  "
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "strat_train_set.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [],
   "source": [
    "housing_labels=strat_train_set['median_house_value'].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [],
   "source": [
    "housing=strat_train_set.drop('median_house_value',axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>ocean_proximity</th>\n",
       "      <th>income_cat</th>\n",
       "      <th>housing_cat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>17606</th>\n",
       "      <td>-121.89</td>\n",
       "      <td>37.29</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1568.0</td>\n",
       "      <td>351.0</td>\n",
       "      <td>710.0</td>\n",
       "      <td>339.0</td>\n",
       "      <td>2.7042</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>18632</th>\n",
       "      <td>-121.93</td>\n",
       "      <td>37.05</td>\n",
       "      <td>14.0</td>\n",
       "      <td>679.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>306.0</td>\n",
       "      <td>113.0</td>\n",
       "      <td>6.4214</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14650</th>\n",
       "      <td>-117.20</td>\n",
       "      <td>32.77</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1952.0</td>\n",
       "      <td>471.0</td>\n",
       "      <td>936.0</td>\n",
       "      <td>462.0</td>\n",
       "      <td>2.8621</td>\n",
       "      <td>NEAR OCEAN</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3230</th>\n",
       "      <td>-119.61</td>\n",
       "      <td>36.31</td>\n",
       "      <td>25.0</td>\n",
       "      <td>1847.0</td>\n",
       "      <td>371.0</td>\n",
       "      <td>1460.0</td>\n",
       "      <td>353.0</td>\n",
       "      <td>1.8839</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3555</th>\n",
       "      <td>-118.59</td>\n",
       "      <td>34.23</td>\n",
       "      <td>17.0</td>\n",
       "      <td>6592.0</td>\n",
       "      <td>1525.0</td>\n",
       "      <td>4459.0</td>\n",
       "      <td>1463.0</td>\n",
       "      <td>3.0347</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
       "17606    -121.89     37.29                38.0       1568.0           351.0   \n",
       "18632    -121.93     37.05                14.0        679.0           108.0   \n",
       "14650    -117.20     32.77                31.0       1952.0           471.0   \n",
       "3230     -119.61     36.31                25.0       1847.0           371.0   \n",
       "3555     -118.59     34.23                17.0       6592.0          1525.0   \n",
       "\n",
       "       population  households  median_income ocean_proximity income_cat  \\\n",
       "17606       710.0       339.0         2.7042       <1H OCEAN          2   \n",
       "18632       306.0       113.0         6.4214       <1H OCEAN          5   \n",
       "14650       936.0       462.0         2.8621      NEAR OCEAN          2   \n",
       "3230       1460.0       353.0         1.8839          INLAND          2   \n",
       "3555       4459.0      1463.0         3.0347       <1H OCEAN          3   \n",
       "\n",
       "      housing_cat  \n",
       "17606           2  \n",
       "18632           5  \n",
       "14650           2  \n",
       "3230            2  \n",
       "3555            3  "
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 16512 entries, 17606 to 15775\n",
      "Data columns (total 11 columns):\n",
      " #   Column              Non-Null Count  Dtype   \n",
      "---  ------              --------------  -----   \n",
      " 0   longitude           16512 non-null  float64 \n",
      " 1   latitude            16512 non-null  float64 \n",
      " 2   housing_median_age  16512 non-null  float64 \n",
      " 3   total_rooms         16512 non-null  float64 \n",
      " 4   total_bedrooms      16354 non-null  float64 \n",
      " 5   population          16512 non-null  float64 \n",
      " 6   households          16512 non-null  float64 \n",
      " 7   median_income       16512 non-null  float64 \n",
      " 8   ocean_proximity     16512 non-null  object  \n",
      " 9   income_cat          16512 non-null  category\n",
      " 10  housing_cat         16512 non-null  category\n",
      "dtypes: category(2), float64(8), object(1)\n",
      "memory usage: 1.3+ MB\n"
     ]
    }
   ],
   "source": [
    "housing.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
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       "      <th>ocean_proximity</th>\n",
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       "  <tbody>\n",
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       "      <th>4629</th>\n",
       "      <td>-118.30</td>\n",
       "      <td>34.07</td>\n",
       "      <td>18.0</td>\n",
       "      <td>3759.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3296.0</td>\n",
       "      <td>1462.0</td>\n",
       "      <td>2.2708</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6068</th>\n",
       "      <td>-117.86</td>\n",
       "      <td>34.01</td>\n",
       "      <td>16.0</td>\n",
       "      <td>4632.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3038.0</td>\n",
       "      <td>727.0</td>\n",
       "      <td>5.1762</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17923</th>\n",
       "      <td>-121.97</td>\n",
       "      <td>37.35</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1955.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>999.0</td>\n",
       "      <td>386.0</td>\n",
       "      <td>4.6328</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13656</th>\n",
       "      <td>-117.30</td>\n",
       "      <td>34.05</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2155.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1039.0</td>\n",
       "      <td>391.0</td>\n",
       "      <td>1.6675</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19252</th>\n",
       "      <td>-122.79</td>\n",
       "      <td>38.48</td>\n",
       "      <td>7.0</td>\n",
       "      <td>6837.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3468.0</td>\n",
       "      <td>1405.0</td>\n",
       "      <td>3.1662</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
       "4629     -118.30     34.07                18.0       3759.0             NaN   \n",
       "6068     -117.86     34.01                16.0       4632.0             NaN   \n",
       "17923    -121.97     37.35                30.0       1955.0             NaN   \n",
       "13656    -117.30     34.05                 6.0       2155.0             NaN   \n",
       "19252    -122.79     38.48                 7.0       6837.0             NaN   \n",
       "\n",
       "       population  households  median_income ocean_proximity income_cat  \\\n",
       "4629       3296.0      1462.0         2.2708       <1H OCEAN          2   \n",
       "6068       3038.0       727.0         5.1762       <1H OCEAN          4   \n",
       "17923       999.0       386.0         4.6328       <1H OCEAN          4   \n",
       "13656      1039.0       391.0         1.6675          INLAND          2   \n",
       "19252      3468.0      1405.0         3.1662       <1H OCEAN          3   \n",
       "\n",
       "      housing_cat  \n",
       "4629            2  \n",
       "6068            4  \n",
       "17923           4  \n",
       "13656           2  \n",
       "19252           3  "
      ]
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rows=housing[housing.isnull().any(axis=1)]\n",
    "rows.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SimpleImputer(strategy='median')"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.impute import SimpleImputer\n",
    "\n",
    "imputer = SimpleImputer(strategy = 'median')\n",
    "housing_num = housing.drop('ocean_proximity', axis =1)\n",
    "imputer.fit(housing_num)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 16512 entries, 17606 to 15775\n",
      "Data columns (total 10 columns):\n",
      " #   Column              Non-Null Count  Dtype   \n",
      "---  ------              --------------  -----   \n",
      " 0   longitude           16512 non-null  float64 \n",
      " 1   latitude            16512 non-null  float64 \n",
      " 2   housing_median_age  16512 non-null  float64 \n",
      " 3   total_rooms         16512 non-null  float64 \n",
      " 4   total_bedrooms      16354 non-null  float64 \n",
      " 5   population          16512 non-null  float64 \n",
      " 6   households          16512 non-null  float64 \n",
      " 7   median_income       16512 non-null  float64 \n",
      " 8   income_cat          16512 non-null  category\n",
      " 9   housing_cat         16512 non-null  category\n",
      "dtypes: category(2), float64(8)\n",
      "memory usage: 1.2 MB\n"
     ]
    }
   ],
   "source": [
    "housing_num.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-118.51  ,   34.26  ,   29.    , 2119.5   ,  433.    , 1164.    ,\n",
       "        408.    ,    3.5409,    3.    ,    3.    ])"
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imputer.statistics_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-121.89  ,   37.29  ,   38.    , ...,    2.7042,    2.    ,\n",
       "           2.    ],\n",
       "       [-121.93  ,   37.05  ,   14.    , ...,    6.4214,    5.    ,\n",
       "           5.    ],\n",
       "       [-117.2   ,   32.77  ,   31.    , ...,    2.8621,    2.    ,\n",
       "           2.    ],\n",
       "       ...,\n",
       "       [-116.4   ,   34.09  ,    9.    , ...,    3.2723,    3.    ,\n",
       "           3.    ],\n",
       "       [-118.01  ,   33.82  ,   31.    , ...,    4.0625,    3.    ,\n",
       "           3.    ],\n",
       "       [-122.45  ,   37.77  ,   52.    , ...,    3.575 ,    3.    ,\n",
       "           3.    ]])"
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X=imputer.transform(housing_num)\n",
    "X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>17606</th>\n",
       "      <td>-121.89</td>\n",
       "      <td>37.29</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1568.0</td>\n",
       "      <td>351.0</td>\n",
       "      <td>710.0</td>\n",
       "      <td>339.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18632</th>\n",
       "      <td>-121.93</td>\n",
       "      <td>37.05</td>\n",
       "      <td>14.0</td>\n",
       "      <td>679.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>306.0</td>\n",
       "      <td>113.0</td>\n",
       "      <td>6.4214</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14650</th>\n",
       "      <td>-117.20</td>\n",
       "      <td>32.77</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1952.0</td>\n",
       "      <td>471.0</td>\n",
       "      <td>936.0</td>\n",
       "      <td>462.0</td>\n",
       "      <td>2.8621</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3230</th>\n",
       "      <td>-119.61</td>\n",
       "      <td>36.31</td>\n",
       "      <td>25.0</td>\n",
       "      <td>1847.0</td>\n",
       "      <td>371.0</td>\n",
       "      <td>1460.0</td>\n",
       "      <td>353.0</td>\n",
       "      <td>1.8839</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3555</th>\n",
       "      <td>-118.59</td>\n",
       "      <td>34.23</td>\n",
       "      <td>17.0</td>\n",
       "      <td>6592.0</td>\n",
       "      <td>1525.0</td>\n",
       "      <td>4459.0</td>\n",
       "      <td>1463.0</td>\n",
       "      <td>3.0347</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
       "17606    -121.89     37.29                38.0       1568.0           351.0   \n",
       "18632    -121.93     37.05                14.0        679.0           108.0   \n",
       "14650    -117.20     32.77                31.0       1952.0           471.0   \n",
       "3230     -119.61     36.31                25.0       1847.0           371.0   \n",
       "3555     -118.59     34.23                17.0       6592.0          1525.0   \n",
       "\n",
       "       population  households  median_income  income_cat  housing_cat  \n",
       "17606       710.0       339.0         2.7042         2.0          2.0  \n",
       "18632       306.0       113.0         6.4214         5.0          5.0  \n",
       "14650       936.0       462.0         2.8621         2.0          2.0  \n",
       "3230       1460.0       353.0         1.8839         2.0          2.0  \n",
       "3555       4459.0      1463.0         3.0347         3.0          3.0  "
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing_train=pd.DataFrame(X,columns=housing_num.columns,index=housing_num.index)\n",
    "housing_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 16512 entries, 17606 to 15775\n",
      "Data columns (total 10 columns):\n",
      " #   Column              Non-Null Count  Dtype  \n",
      "---  ------              --------------  -----  \n",
      " 0   longitude           16512 non-null  float64\n",
      " 1   latitude            16512 non-null  float64\n",
      " 2   housing_median_age  16512 non-null  float64\n",
      " 3   total_rooms         16512 non-null  float64\n",
      " 4   total_bedrooms      16512 non-null  float64\n",
      " 5   population          16512 non-null  float64\n",
      " 6   households          16512 non-null  float64\n",
      " 7   median_income       16512 non-null  float64\n",
      " 8   income_cat          16512 non-null  float64\n",
      " 9   housing_cat         16512 non-null  float64\n",
      "dtypes: float64(10)\n",
      "memory usage: 1.4 MB\n"
     ]
    }
   ],
   "source": [
    "housing_train.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ocean_proximity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>17606</th>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18632</th>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14650</th>\n",
       "      <td>NEAR OCEAN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3230</th>\n",
       "      <td>INLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3555</th>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19480</th>\n",
       "      <td>INLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8879</th>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13685</th>\n",
       "      <td>INLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4937</th>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4861</th>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      ocean_proximity\n",
       "17606       <1H OCEAN\n",
       "18632       <1H OCEAN\n",
       "14650      NEAR OCEAN\n",
       "3230           INLAND\n",
       "3555        <1H OCEAN\n",
       "19480          INLAND\n",
       "8879        <1H OCEAN\n",
       "13685          INLAND\n",
       "4937        <1H OCEAN\n",
       "4861        <1H OCEAN"
      ]
     },
     "execution_count": 141,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing_cat = housing[['ocean_proximity']]\n",
    "housing_cat.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<1H OCEAN     7276\n",
       "INLAND        5263\n",
       "NEAR OCEAN    2124\n",
       "NEAR BAY      1847\n",
       "ISLAND           2\n",
       "Name: ocean_proximity, dtype: int64"
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing['ocean_proximity'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 4, ..., 1, 0, 3])"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.preprocessing import LabelEncoder\n",
    "encoder = LabelEncoder()\n",
    "housing_cat = housing['ocean_proximity']\n",
    "housing_cat_encoder = encoder.fit_transform(housing_cat)\n",
    "housing_cat_encoder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['<1H OCEAN', 'INLAND', 'ISLAND', 'NEAR BAY', 'NEAR OCEAN'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 146,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "encoder.classes_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import OneHotEncoder\n",
    "encoder=OneHotEncoder()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0],\n",
       "       [0],\n",
       "       [4],\n",
       "       ...,\n",
       "       [1],\n",
       "       [0],\n",
       "       [3]])"
      ]
     },
     "execution_count": 148,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing_cat_encoder.reshape(-1,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [],
   "source": [
    "housing_cat_hot=encoder.fit_transform(housing_cat_encoder.reshape(-1,1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<16512x5 sparse matrix of type '<class 'numpy.float64'>'\n",
       "\twith 16512 stored elements in Compressed Sparse Row format>"
      ]
     },
     "execution_count": 150,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing_cat_hot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1., 0., 0., 0., 0.],\n",
       "       [1., 0., 0., 0., 0.],\n",
       "       [0., 0., 0., 0., 1.],\n",
       "       ...,\n",
       "       [0., 1., 0., 0., 0.],\n",
       "       [1., 0., 0., 0., 0.],\n",
       "       [0., 0., 0., 1., 0.]])"
      ]
     },
     "execution_count": 151,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing_cat_hot.toarray()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1, 0, 0, 0, 0],\n",
       "       [1, 0, 0, 0, 0],\n",
       "       [0, 0, 0, 0, 1],\n",
       "       ...,\n",
       "       [0, 1, 0, 0, 0],\n",
       "       [1, 0, 0, 0, 0],\n",
       "       [0, 0, 0, 1, 0]])"
      ]
     },
     "execution_count": 153,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.preprocessing import LabelBinarizer\n",
    "encoder = LabelBinarizer()\n",
    "housing_cat_1hot = encoder.fit_transform(housing_cat)\n",
    "housing_cat_1hot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<16512x5 sparse matrix of type '<class 'numpy.int64'>'\n",
       "\twith 16512 stored elements in Compressed Sparse Row format>"
      ]
     },
     "execution_count": 154,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.preprocessing import LabelBinarizer\n",
    "encoder = LabelBinarizer(sparse_output = True)\n",
    "housing_cat_1hot = encoder.fit_transform(housing_cat)\n",
    "housing_cat_1hot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "17606     <1H OCEAN\n",
       "18632     <1H OCEAN\n",
       "14650    NEAR OCEAN\n",
       "3230         INLAND\n",
       "3555      <1H OCEAN\n",
       "            ...    \n",
       "6563         INLAND\n",
       "12053        INLAND\n",
       "13908        INLAND\n",
       "11159     <1H OCEAN\n",
       "15775      NEAR BAY\n",
       "Name: ocean_proximity, Length: 16512, dtype: object"
      ]
     },
     "execution_count": 152,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing_cat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.base import BaseEstimator, TransformerMixin\n",
    "\n",
    "\n",
    "rooms_ix, bedrooms_ix, population_ix, household_ix = [list(housing.columns).index(col) for col in (\"total_rooms\", \"total_bedrooms\", \"population\", \"households\")]\n",
    "rooms_ix, bedrooms_ix, population_ix, household_ix \n",
    "class CombinedAttributesAdder(BaseEstimator, TransformerMixin):\n",
    "    def __init__(self, add_bedrooms_per_room = True):\n",
    "        self.add_bedrooms_per_room = add_bedrooms_per_room\n",
    "    def fit(self, X, y = None):\n",
    "        return self\n",
    "    def transform(self, X, y = None):\n",
    "        rooms_per_household = X[:, rooms_ix] / X[:, household_ix]\n",
    "        population_per_household = X[:, population_ix] / X[:, household_ix]\n",
    "        if self.add_bedrooms_per_room:\n",
    "            bedrooms_per_room = X[:, bedrooms_ix] / X[:, rooms_ix]\n",
    "            return np.c_[X, rooms_per_household,population_per_household, bedrooms_per_room]\n",
    "        else:\n",
    "            return np.c_[X, rooms_per_household,population_per_household]\n",
    "        \n",
    "        \n",
    "        \n",
    "attr_adder = CombinedAttributesAdder(add_bedrooms_per_room = False)\n",
    "housing_extra_attribs = attr_adder.transform(housing.values)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housing_median_age</th>\n",
       "      <th>total_rooms</th>\n",
       "      <th>total_bedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>median_income</th>\n",
       "      <th>ocean_proximity</th>\n",
       "      <th>income_cat</th>\n",
       "      <th>housing_cat</th>\n",
       "      <th>rooms_per_household</th>\n",
       "      <th>population_per_household</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>17606</th>\n",
       "      <td>-121.89</td>\n",
       "      <td>37.29</td>\n",
       "      <td>38</td>\n",
       "      <td>1568</td>\n",
       "      <td>351</td>\n",
       "      <td>710</td>\n",
       "      <td>339</td>\n",
       "      <td>2.7042</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>4.62537</td>\n",
       "      <td>2.0944</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18632</th>\n",
       "      <td>-121.93</td>\n",
       "      <td>37.05</td>\n",
       "      <td>14</td>\n",
       "      <td>679</td>\n",
       "      <td>108</td>\n",
       "      <td>306</td>\n",
       "      <td>113</td>\n",
       "      <td>6.4214</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>6.00885</td>\n",
       "      <td>2.70796</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14650</th>\n",
       "      <td>-117.2</td>\n",
       "      <td>32.77</td>\n",
       "      <td>31</td>\n",
       "      <td>1952</td>\n",
       "      <td>471</td>\n",
       "      <td>936</td>\n",
       "      <td>462</td>\n",
       "      <td>2.8621</td>\n",
       "      <td>NEAR OCEAN</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>4.22511</td>\n",
       "      <td>2.02597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3230</th>\n",
       "      <td>-119.61</td>\n",
       "      <td>36.31</td>\n",
       "      <td>25</td>\n",
       "      <td>1847</td>\n",
       "      <td>371</td>\n",
       "      <td>1460</td>\n",
       "      <td>353</td>\n",
       "      <td>1.8839</td>\n",
       "      <td>INLAND</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>5.23229</td>\n",
       "      <td>4.13598</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3555</th>\n",
       "      <td>-118.59</td>\n",
       "      <td>34.23</td>\n",
       "      <td>17</td>\n",
       "      <td>6592</td>\n",
       "      <td>1525</td>\n",
       "      <td>4459</td>\n",
       "      <td>1463</td>\n",
       "      <td>3.0347</td>\n",
       "      <td>&lt;1H OCEAN</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4.50581</td>\n",
       "      <td>3.04785</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      longitude latitude housing_median_age total_rooms total_bedrooms  \\\n",
       "17606   -121.89    37.29                 38        1568            351   \n",
       "18632   -121.93    37.05                 14         679            108   \n",
       "14650    -117.2    32.77                 31        1952            471   \n",
       "3230    -119.61    36.31                 25        1847            371   \n",
       "3555    -118.59    34.23                 17        6592           1525   \n",
       "\n",
       "      population households median_income ocean_proximity income_cat  \\\n",
       "17606        710        339        2.7042       <1H OCEAN          2   \n",
       "18632        306        113        6.4214       <1H OCEAN          5   \n",
       "14650        936        462        2.8621      NEAR OCEAN          2   \n",
       "3230        1460        353        1.8839          INLAND          2   \n",
       "3555        4459       1463        3.0347       <1H OCEAN          3   \n",
       "\n",
       "      housing_cat rooms_per_household population_per_household  \n",
       "17606           2             4.62537                   2.0944  \n",
       "18632           5             6.00885                  2.70796  \n",
       "14650           2             4.22511                  2.02597  \n",
       "3230            2             5.23229                  4.13598  \n",
       "3555            3             4.50581                  3.04785  "
      ]
     },
     "execution_count": 157,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing_extra_attribs = pd.DataFrame(\n",
    "    housing_extra_attribs,\n",
    "    columns=list(housing.columns)+[\"rooms_per_household\", \"population_per_household\"],\n",
    "    index=housing.index)\n",
    "housing_extra_attribs.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "num_pipeline = Pipeline([\n",
    "        ('imputer', SimpleImputer(strategy=\"median\")),\n",
    "        ('attribs_adder', CombinedAttributesAdder()),\n",
    "        ('std_scaler', StandardScaler())\n",
    "    ])\n",
    "\n",
    "housing_num_tr = num_pipeline.fit_transform(housing_num)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {},
   "outputs": [],
   "source": [
    "class DataFrameSelector(BaseEstimator, TransformerMixin):\n",
    "    def __init__(self, attribute_names):\n",
    "        self.attribute_names = attribute_names\n",
    "    def fit(self, X, y=None):\n",
    "        return self\n",
    "    def transform(self, X):\n",
    "        return X[self.attribute_names].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [],
   "source": [
    "num_attribs =list(housing_num) \n",
    "num_pipeline = Pipeline([\n",
    "        ('selector', DataFrameSelector(num_attribs)),\n",
    "        ('imputer', SimpleImputer(strategy=\"median\")),\n",
    "        ('attribs_adder', CombinedAttributesAdder()),\n",
    "        ('std_scaler', StandardScaler()),\n",
    "    ])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.base import TransformerMixin \n",
    "class MyLabelBinarizer(TransformerMixin):\n",
    "    def __init__(self, *args, **kwargs):\n",
    "        self.encoder = LabelBinarizer(*args, **kwargs)\n",
    "    def fit(self, x, y=0):\n",
    "        self.encoder.fit(x)\n",
    "        return self\n",
    "    def transform(self, x, y=0):\n",
    "        return self.encoder.transform(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [],
   "source": [
    "cat_attribs = ['ocean_proximity']\n",
    "from sklearn.preprocessing import LabelBinarizer\n",
    "\n",
    "cat_pipeline = Pipeline([\n",
    "        ('selector', DataFrameSelector(cat_attribs)),               \n",
    "        ('LabelBinarizer', MyLabelBinarizer()),\n",
    "    ])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.pipeline import FeatureUnion\n",
    "\n",
    "full_pipeline = FeatureUnion(transformer_list=[\n",
    "        (\"num_pipline\", num_pipeline,),\n",
    "        ('cat_pipline', cat_pipeline),\n",
    "    ])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-1.15604281,  0.77194962,  0.74333089, ...,  0.        ,\n",
       "         0.        ,  0.        ],\n",
       "       [-1.17602483,  0.6596948 , -1.1653172 , ...,  0.        ,\n",
       "         0.        ,  0.        ],\n",
       "       [ 1.18684903, -1.34218285,  0.18664186, ...,  0.        ,\n",
       "         0.        ,  1.        ],\n",
       "       ...,\n",
       "       [ 1.58648943, -0.72478134, -1.56295222, ...,  0.        ,\n",
       "         0.        ,  0.        ],\n",
       "       [ 0.78221312, -0.85106801,  0.18664186, ...,  0.        ,\n",
       "         0.        ,  0.        ],\n",
       "       [-1.43579109,  0.99645926,  1.85670895, ...,  0.        ,\n",
       "         1.        ,  0.        ]])"
      ]
     },
     "execution_count": 167,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing_finished=full_pipeline.fit_transform(housing)\n",
    "housing_finished"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "      <th>13</th>\n",
       "      <th>14</th>\n",
       "      <th>15</th>\n",
       "      <th>16</th>\n",
       "      <th>17</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-1.156043</td>\n",
       "      <td>0.771950</td>\n",
       "      <td>0.743331</td>\n",
       "      <td>-0.493234</td>\n",
       "      <td>-0.445438</td>\n",
       "      <td>-0.636211</td>\n",
       "      <td>-0.420698</td>\n",
       "      <td>-0.614937</td>\n",
       "      <td>-0.954456</td>\n",
       "      <td>-0.954456</td>\n",
       "      <td>-0.312055</td>\n",
       "      <td>-0.086499</td>\n",
       "      <td>0.155318</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-1.176025</td>\n",
       "      <td>0.659695</td>\n",
       "      <td>-1.165317</td>\n",
       "      <td>-0.908967</td>\n",
       "      <td>-1.036928</td>\n",
       "      <td>-0.998331</td>\n",
       "      <td>-1.022227</td>\n",
       "      <td>1.336459</td>\n",
       "      <td>1.890305</td>\n",
       "      <td>1.890305</td>\n",
       "      <td>0.217683</td>\n",
       "      <td>-0.033534</td>\n",
       "      <td>-0.836289</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.186849</td>\n",
       "      <td>-1.342183</td>\n",
       "      <td>0.186642</td>\n",
       "      <td>-0.313660</td>\n",
       "      <td>-0.153345</td>\n",
       "      <td>-0.433639</td>\n",
       "      <td>-0.093318</td>\n",
       "      <td>-0.532046</td>\n",
       "      <td>-0.954456</td>\n",
       "      <td>-0.954456</td>\n",
       "      <td>-0.465315</td>\n",
       "      <td>-0.092405</td>\n",
       "      <td>0.422200</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.017068</td>\n",
       "      <td>0.313576</td>\n",
       "      <td>-0.290520</td>\n",
       "      <td>-0.362762</td>\n",
       "      <td>-0.396756</td>\n",
       "      <td>0.036041</td>\n",
       "      <td>-0.383436</td>\n",
       "      <td>-1.045566</td>\n",
       "      <td>-0.954456</td>\n",
       "      <td>-0.954456</td>\n",
       "      <td>-0.079661</td>\n",
       "      <td>0.089736</td>\n",
       "      <td>-0.196453</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.492474</td>\n",
       "      <td>-0.659299</td>\n",
       "      <td>-0.926736</td>\n",
       "      <td>1.856193</td>\n",
       "      <td>2.412211</td>\n",
       "      <td>2.724154</td>\n",
       "      <td>2.570975</td>\n",
       "      <td>-0.441437</td>\n",
       "      <td>-0.006202</td>\n",
       "      <td>-0.006202</td>\n",
       "      <td>-0.357834</td>\n",
       "      <td>-0.004194</td>\n",
       "      <td>0.269928</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         0         1         2         3         4         5         6   \\\n",
       "0 -1.156043  0.771950  0.743331 -0.493234 -0.445438 -0.636211 -0.420698   \n",
       "1 -1.176025  0.659695 -1.165317 -0.908967 -1.036928 -0.998331 -1.022227   \n",
       "2  1.186849 -1.342183  0.186642 -0.313660 -0.153345 -0.433639 -0.093318   \n",
       "3 -0.017068  0.313576 -0.290520 -0.362762 -0.396756  0.036041 -0.383436   \n",
       "4  0.492474 -0.659299 -0.926736  1.856193  2.412211  2.724154  2.570975   \n",
       "\n",
       "         7         8         9         10        11        12   13   14   15  \\\n",
       "0 -0.614937 -0.954456 -0.954456 -0.312055 -0.086499  0.155318  1.0  0.0  0.0   \n",
       "1  1.336459  1.890305  1.890305  0.217683 -0.033534 -0.836289  1.0  0.0  0.0   \n",
       "2 -0.532046 -0.954456 -0.954456 -0.465315 -0.092405  0.422200  0.0  0.0  0.0   \n",
       "3 -1.045566 -0.954456 -0.954456 -0.079661  0.089736 -0.196453  0.0  1.0  0.0   \n",
       "4 -0.441437 -0.006202 -0.006202 -0.357834 -0.004194  0.269928  1.0  0.0  0.0   \n",
       "\n",
       "    16   17  \n",
       "0  0.0  0.0  \n",
       "1  0.0  0.0  \n",
       "2  0.0  1.0  \n",
       "3  0.0  0.0  \n",
       "4  0.0  0.0  "
      ]
     },
     "execution_count": 169,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing_final = pd.DataFrame(housing_finished)\n",
    "housing_final.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "17606    286600.0\n",
       "18632    340600.0\n",
       "14650    196900.0\n",
       "3230      46300.0\n",
       "3555     254500.0\n",
       "           ...   \n",
       "6563     240200.0\n",
       "12053    113000.0\n",
       "13908     97800.0\n",
       "11159    225900.0\n",
       "15775    500001.0\n",
       "Name: median_house_value, Length: 16512, dtype: float64"
      ]
     },
     "execution_count": 172,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(housing_final)\n",
    "df.head()\n",
    "housing_labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 174,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#用线性回归模型\n",
    "from sklearn.linear_model import LinearRegression\n",
    "lin_reg = LinearRegression()\n",
    "lin_reg.fit(housing_final, housing_labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predictions: [203682.37379543 326371.39370781 204218.64588245  58685.4770482\n",
      " 194213.06443039]\n",
      "17606    286600.0\n",
      "18632    340600.0\n",
      "14650    196900.0\n",
      "3230      46300.0\n",
      "3555     254500.0\n",
      "Name: median_house_value, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "some_data = housing.iloc[:5]\n",
    "some_data_prepared = full_pipeline.transform(some_data)\n",
    "\n",
    "print(\"Predictions:\", lin_reg.predict(some_data_prepared))\n",
    "print(housing_labels.iloc[:5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "68376.64295459937"
      ]
     },
     "execution_count": 186,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#对模型进行预测误差\n",
    "from sklearn.metrics import mean_squared_error\n",
    "\n",
    "housing_predictions = lin_reg.predict(housing_final)\n",
    "lin_mse = mean_squared_error(housing_labels, housing_predictions)\n",
    "lin_mse\n",
    "lin_rmse = np.sqrt(lin_mse)\n",
    "lin_rmse"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 误差高达68376，对训练数据拟合不足"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DecisionTreeRegressor(random_state=42)"
      ]
     },
     "execution_count": 201,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#决策树\n",
    "from sklearn.tree import DecisionTreeRegressor\n",
    "\n",
    "tree_reg = DecisionTreeRegressor(random_state=42)\n",
    "tree_reg.fit(housing_final, housing_labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0"
      ]
     },
     "execution_count": 196,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing_predictions=tree_reg.predict(housing_final)\n",
    "tree_mse = mean_squared_error(housing_labels, housing_predictions)\n",
    "tree_rmse = np.sqrt(tree_mse)\n",
    "tree_rmse"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 误差为0 可能是模型对训练数据的过度拟合"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "metadata": {},
   "outputs": [],
   "source": [
    "#使用交叉验证进行更好的评估"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([67731.66215134, 68320.70005304, 70619.20405172, 68869.88367615,\n",
       "       71640.50664542, 75401.54284899, 70418.78036278, 70458.16586321,\n",
       "       78067.50776057, 68905.47973957])"
      ]
     },
     "execution_count": 210,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.model_selection import cross_val_score\n",
    "scores = cross_val_score(tree_reg, housing_final, housing_labels,\n",
    "                         scoring=\"neg_mean_squared_error\", cv=10)\n",
    "tree_rmse_scores = np.sqrt(-scores)\n",
    "tree_rmse_scores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 207,
   "metadata": {},
   "outputs": [],
   "source": [
    "def display_scores(scores):\n",
    "    print(\"Scores:\", scores)\n",
    "    print(\"Mean:\", scores.mean())\n",
    "    print(\"Standard deviation:\", scores.std())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Scores: [67731.66215134 68320.70005304 70619.20405172 68869.88367615\n",
      " 71640.50664542 75401.54284899 70418.78036278 70458.16586321\n",
      " 78067.50776057 68905.47973957]\n",
      "Mean: 71043.34331527856\n",
      "Standard deviation: 3118.9133517320333\n"
     ]
    }
   ],
   "source": [
    "display_scores(tree_rmse_scores)\n",
    "#决策树交叉验证的结果"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Scores: [66877.52325028 66608.120256   70575.91118868 74179.94799352\n",
      " 67683.32205678 71103.16843468 64782.65896552 67711.29940352\n",
      " 71080.40484136 67687.6384546 ]\n",
      "Mean: 68828.9994844933\n",
      "Standard deviation: 2662.761570610341\n"
     ]
    }
   ],
   "source": [
    "lin_scores = cross_val_score(lin_reg, housing_final, housing_labels,\n",
    "                             scoring=\"neg_mean_squared_error\", cv=10)\n",
    "lin_rmse_scores = np.sqrt(-lin_scores)\n",
    "display_scores(lin_rmse_scores)\n",
    "#线性回归 交叉验证的结果"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 随机森林"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 222,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RandomForestRegressor(n_estimators=10, random_state=42)"
      ]
     },
     "execution_count": 222,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestRegressor\n",
    "forest_reg=RandomForestRegressor(n_estimators=10,random_state=42)\n",
    "forest_reg.fit(housing_final,housing_labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 223,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "22079.264772915525"
      ]
     },
     "execution_count": 223,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "housing_predictions=forest_reg.predict(housing_final)\n",
    "forest_mse=mean_squared_error(housing_labels,housing_predictions)\n",
    "forest_rmse=np.sqrt(forest_mse)\n",
    "forest_rmse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "metadata": {},
   "outputs": [],
   "source": [
    "forest_scores=cross_val_score(forest_reg,housing_final,housing_labels,scoring=\"neg_mean_squared_error\", cv=10)\n",
    "forest_rmse_scores=np.sqrt(-forest_scores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 219,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Scores: [51271.49013154 49324.11111634 54031.70434442 54548.95216212\n",
      " 50855.15148747 56134.30351177 51727.50312514 49723.9218968\n",
      " 55438.1089786  53247.64628448]\n",
      "Mean: 52630.28930386873\n",
      "Standard deviation: 2266.6844921824913\n"
     ]
    }
   ],
   "source": [
    "display_scores(forest_rmse_scores)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 寻找最佳参数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 266,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GridSearchCV(cv=5, estimator=RandomForestRegressor(random_state=42),\n",
       "             param_grid=[{'max_features': [2, 4, 6, 8],\n",
       "                          'n_estimators': [3, 10, 30]},\n",
       "                         {'bootstrap': [False], 'max_features': [2, 3, 4],\n",
       "                          'n_estimators': [3, 10]}],\n",
       "             return_train_score=True, scoring='neg_mean_squared_error')"
      ]
     },
     "execution_count": 266,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.model_selection import GridSearchCV\n",
    "\n",
    "param_grid = [\n",
    "    {'n_estimators': [3, 10, 30], 'max_features': [2, 4, 6, 8]},\n",
    "    {'bootstrap': [False], 'n_estimators': [3, 10], 'max_features': [2, 3, 4]},\n",
    "  ]\n",
    "\n",
    "forest_reg = RandomForestRegressor(random_state=42)\n",
    "grid_search = GridSearchCV(forest_reg, param_grid, cv=5,\n",
    "                           scoring='neg_mean_squared_error', return_train_score=True)\n",
    "grid_search.fit(housing_final, housing_labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 267,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'max_features': 8, 'n_estimators': 30}"
      ]
     },
     "execution_count": 267,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grid_search.best_params_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 268,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RandomForestRegressor(max_features=8, n_estimators=30, random_state=42)"
      ]
     },
     "execution_count": 268,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grid_search.best_estimator_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 269,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "64303.7636095493 {'max_features': 2, 'n_estimators': 3}\n",
      "55693.256394559416 {'max_features': 2, 'n_estimators': 10}\n",
      "53459.425150186566 {'max_features': 2, 'n_estimators': 30}\n",
      "61364.959494456314 {'max_features': 4, 'n_estimators': 3}\n",
      "53685.433417673245 {'max_features': 4, 'n_estimators': 10}\n",
      "51751.58375488621 {'max_features': 4, 'n_estimators': 30}\n",
      "60661.64571528491 {'max_features': 6, 'n_estimators': 3}\n",
      "53918.163214989814 {'max_features': 6, 'n_estimators': 10}\n",
      "51550.54635316932 {'max_features': 6, 'n_estimators': 30}\n",
      "59241.08077549724 {'max_features': 8, 'n_estimators': 3}\n",
      "53009.94131770102 {'max_features': 8, 'n_estimators': 10}\n",
      "50943.90229195784 {'max_features': 8, 'n_estimators': 30}\n",
      "63227.24188951435 {'bootstrap': False, 'max_features': 2, 'n_estimators': 3}\n",
      "54520.11000786228 {'bootstrap': False, 'max_features': 2, 'n_estimators': 10}\n",
      "60865.23550479907 {'bootstrap': False, 'max_features': 3, 'n_estimators': 3}\n",
      "54196.31216560988 {'bootstrap': False, 'max_features': 3, 'n_estimators': 10}\n",
      "58914.47811147827 {'bootstrap': False, 'max_features': 4, 'n_estimators': 3}\n",
      "52584.72225061174 {'bootstrap': False, 'max_features': 4, 'n_estimators': 10}\n"
     ]
    }
   ],
   "source": [
    "cvres = grid_search.cv_results_\n",
    "for mean_score, params in zip(cvres[\"mean_test_score\"], cvres[\"params\"]):\n",
    "    print(np.sqrt(-mean_score), params)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 随机搜素最佳参数 （工程量大 且边际递减）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import RandomizedSearchCV\n",
    "from scipy.stats import randint\n",
    "\n",
    "param_distribs = {\n",
    "        'n_estimators': randint(low=1, high=200),\n",
    "        'max_features': randint(low=1, high=8),\n",
    "    }\n",
    "\n",
    "forest_reg = RandomForestRegressor(random_state=42)\n",
    "rnd_search = RandomizedSearchCV(forest_reg, param_distributions=param_distribs,\n",
    "                                n_iter=10, cv=5, scoring='neg_mean_squared_error', random_state=42)\n",
    "rnd_search.fit(housing_final, housing_labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "cvres = rnd_search.cv_results_\n",
    "for mean_score, params in zip(cvres[\"mean_test_score\"], cvres[\"params\"]):\n",
    "    print(np.sqrt(-mean_score), params)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 270,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([6.35547503e-02, 5.26169451e-02, 4.72235877e-02, 1.61839599e-02,\n",
       "       1.67149663e-02, 1.74079009e-02, 1.63586628e-02, 2.59591413e-01,\n",
       "       9.73368134e-02, 9.93932574e-02, 3.52547623e-02, 1.07432806e-01,\n",
       "       3.40881687e-02, 5.83812855e-03, 1.24377910e-01, 1.31956849e-04,\n",
       "       2.55220528e-03, 3.94180571e-03])"
      ]
     },
     "execution_count": 270,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feature_importances = grid_search.best_estimator_.feature_importances_\n",
    "feature_importances"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 271,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0.25959141265711155, 'median_income'),\n",
       " (0.1243779102397659, '广东省'),\n",
       " (0.10743280589772906, 'population_per_household'),\n",
       " (0.09939325735708224, 'housing_cat'),\n",
       " (0.09733681339078402, 'income_cat'),\n",
       " (0.06355475032599624, 'longitude'),\n",
       " (0.052616945105444714, 'latitude'),\n",
       " (0.0472235876558832, 'housing_median_age'),\n",
       " (0.035254762316690606, 'rooms_per_household'),\n",
       " (0.03408816871393459, 'bedrooms_per_room'),\n",
       " (0.017407900936513253, 'population'),\n",
       " (0.01671496628753121, 'total_bedrooms'),\n",
       " (0.01635866279628574, 'households'),\n",
       " (0.016183959929610796, 'total_rooms'),\n",
       " (0.005838128554385691, '北京市'),\n",
       " (0.002552205275047457, '湖南省'),\n",
       " (0.00013195684910495694, '河北省')]"
      ]
     },
     "execution_count": 271,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "extra_attribs = [\"rooms_per_household\", \"population_per_household\", \"bedrooms_per_room\"]\n",
    "cat_one_hot_attribs = list(encoder.classes_)\n",
    "attributes = num_attribs + extra_attribs + cat_one_hot_attribs\n",
    "sorted(zip(feature_importances, attributes), reverse = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 272,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "49608.66765162641"
      ]
     },
     "execution_count": 272,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_model = grid_search.best_estimator_\n",
    "\n",
    "X_test = strat_test_set.drop('median_house_value', axis = 1)\n",
    "y_test = strat_test_set['median_house_value'].copy()\n",
    "\n",
    "X_test_prepared = full_pipeline.transform(X_test)\n",
    "\n",
    "final_predictions = final_model.predict(X_test_prepared)\n",
    "\n",
    "final_mse = mean_squared_error(y_test, final_predictions)\n",
    "final_rmse = np.sqrt(final_mse)\n",
    "final_rmse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 代码语法太难理解了 拓展题不会"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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